Garry Kasparov playing against Deep Blue, the first machine to win a chess match against a reigning world champion. Garry Kasparov (Га́рри Ки́мович Каспа́ров) (born as Garry Kimovich Weinstein on April 13 1963 in Baku, Azerbaijan SSR, Soviet Deep Blue is a Chess - playing Computer developed by IBM. On 11 May 1997, the machine won a six-game match by two wins to

Artificial intelligence (AI) is both the intelligence of machines and the branch of computer science which aims to create it. Intelligence (also called intellect) is an Umbrella term used to describe a property of the Mind that encompasses many related abilities such as the capacities Computer science (or computing science) is the study and the Science of the theoretical foundations of Information and Computation and their

Major AI textbooks define artificial intelligence as "the study and design of intelligent agents,"^[1] where an intelligent agent is a system that perceives its environment and takes actions which maximize its chances of success. In Artificial intelligence, an intelligent agent ( IA) is an entity which observes "reason" and acts upon an environment (i In Artificial intelligence, an intelligent agent ( IA) is an entity which observes "reason" and acts upon an environment (i ^[2] AI can be seen as a realization of an abstract intelligent agent (AIA) which exhibits the functional essence of intelligence. ^[3] John McCarthy, who coined the term in 1956,^[4] defines it as "the science and engineering of making intelligent machines. John McCarthy (born September 4, 1927, in Boston, Massachusetts) is an American Computer scientist and Cognitive "^[5]

Among the traits that researchers hope machines will exhibit are reasoning, knowledge, planning, learning, communication, perception and the ability to move and manipulate objects. ^[6] General intelligence (or "strong AI") has not yet been achieved and is a long-term goal of AI research. Strong AI is Artificial intelligence that matches or exceeds human intelligence —the intelligence of a machine that can successfully perform any intellectual task ^[7]

AI research uses tools and insights from many fields, including computer science, psychology, philosophy, neuroscience, cognitive science, linguistics, ontology, operations research, economics, control theory, probability, optimization and logic. Computer science (or computing science) is the study and the Science of the theoretical foundations of Information and Computation and their Psychology (from Greek grc ψῡχή psȳkhē, "breath life soul" and grc -λογία -logia) is an Academic and Philosophy is the study of general problems concerning matters such as existence knowledge truth beauty justice validity mind and language Neuroscience is a field devoted to the scientific study of the nervous system Cognitive science may be broadly defined as the multidisciplinary study of mind and behavior Computational linguistics is an Interdisciplinary field dealing with the statistical and/or rule-based modeling of Natural language from a computational An ontology in both Computer science and Information science is a formal representation of a set of concepts within a domain and the relationships between Operations Research (OR in North America South Africa and Australia and Operational Research in Europe is an interdisciplinary branch of applied Mathematics and Computational economics explores the intersection of economics and computation Control theory is an interdisciplinary branch of Engineering and Mathematics, that deals with the behavior of Dynamical systems The desired output Probability is the likelihood or chance that something is the case or will happen In Mathematics, the term optimization, or mathematical programming, refers to the study of problems in which one seeks to minimize or maximize a real function Logic is the study of the principles of valid demonstration and Inference. ^[8] AI research also overlaps with tasks such as robotics, control systems, scheduling, data mining, logistics, speech recognition, facial recognition and many others. See also Robot Robotics is the science and technology of Robots and their design manufacture and application A control system is a device or set of devices to manage command direct or regulate the behavior of other devices or systems Automated planning and scheduling is a branch of Artificial intelligence that concerns the realisation of strategies or action sequences typically for execution by Data mining is the process of Sorting through large amounts of data and picking out relevant information Logistics is the management of the flow of Goods, Information and other resources including Energy and people between the point of origin and the point Speech recognition (also known as automatic speech recognition or computer speech recognition) converts spoken words to machine-readable input (for example to keypresses A facial recognition system is a computer application for automatically identifying or verifying a person from a digital image or a video frame from a video source ^[9] Other names for the field have been proposed, such as computational intelligence,^[10] synthetic intelligence,^[10] intelligent systems,^[11] or computational rationality. Computational intelligence (CI is an offshoot of Artificial intelligence. Synthetic intelligence (SI is an alternative term for Artificial intelligence. ^[12]

Perspectives on AI

AI in myth, fiction and speculation

Main articles: artificial intelligence in fiction, ethics of artificial intelligence, transhumanism, and Technological singularity

Humanity has imagined in great detail the implications of thinking machines or artificial beings. This is a sub-article of Artificial intelligence (AI, describing the different futuristic portrayals of fictional artificial intelligence in books and film Treating AIs Ethically There are many ethical problems associated with working to create intelligent creatures Transhumanism (sometimes symbolized by >H or H+) a term often used as a synonym for " Human enhancement " is an international intellectual The technological singularity is a theoretical future point of unprecedented technological progress caused in part by the ability of machines to improve themselves using Artificial They appear in Greek myths, such as Talos of Crete, the golden robots of Hephaestus and Pygmalion's Galatea. Greek mythology is the body of stories belonging to the ancient Greeks concerning their gods and Heroes the nature of the world and the origins and significance In the Cretan tales incorporated into Greek mythology, Tálos (Greek Τάλως Latin Talus or Tálon (Greek Τάλων was a giant man of bronze Crete ( Greek: Κρήτη transliteration: Krētē, modern transliteration Kriti) is the largest of the Greek islands and the Hephaestus (hɨˈfiːstəs or /hɨˈfɛstəs/ Greek Hēphaistos) was a Greek god whose Roman equivalent was Vulcan. Pygmalion is a Legendary figure of Cyprus. Though Pygmalion is the Greek version of the Phoenician royal name Pumayyaton, he is most For the Sicilian Nereid in love with Acis, see Acis and Galatea (mythology For the wife of Lamprus, who prayed to ^[13] The earliest known humanoid robots (or automatons) were sacred statues worshipped in Egypt and Greece, believed to have been endowed with genuine consciousness by craftsman. This article is about a self-operating machine For other uses of Automaton see Automaton (disambiguation or Automata (disambiguation. In the practice of Religion, a cult image is a man-made object that is venerated for the Deity, spirit or Daemon that it embodies or represents This article is about the country of Egypt For a topic outline on this subject see List of basic Egypt topics. Greece (Ελλάδα transliterated: Elláda, historically, Ellás,) officially the Hellenic Republic (Ελληνική Δημοκρατία ^[14] In medieval times, alchemists such as Paracelsus claimed to have created artificial beings. Paracelsus (11 November or 17 December 1493 in Einsiedeln Switzerland – 24 September 1541 in Salzburg, Austria) was an alchemist, ^[15] Realistic clockwork imitations of human beings have been built by people such as Yan Shi,^[16] Hero of Alexandria,^[17] Al-Jazari^[18] and Wolfgang von Kempelen. King Mu of Zhou ( ch 周穆王 Zhōu Mù Wáng or King Mu of Chou or Mu Wang was the fifth sovereign of the Chinese Zhou Dynasty. Hero (or Heron) of Alexandria ( Ήρων ο Αλεξανδρεύς) (c Abū al-'Iz Ibn Ismā'īl ibn al-Razāz al-Jazarī ( 1136 - 1206) (أَبُو اَلْعِزِ بْنُ إسْماعِيلِ بْنُ الرِّزاز الجزري ^[19] Pamela McCorduck observes that "artificial intelligence in one form or another is an idea that has pervaded Western intellectual history, a dream in urgent need of being realized. "^[20]

In modern fiction, beginning with Mary Shelley's classic Frankenstein, writers have explored the ethical issues presented by thinking machines. Mary Shelley ( Née Mary Wollstonecraft Godwin; 30 August Frankenstein or The Modern Prometheus, generally known as Frankenstein, is a Novel written by the British author Mary Shelley Treating AIs Ethically There are many ethical problems associated with working to create intelligent creatures ^[21] If a machine can be created that has intelligence, can it also feel? If it can feel, does it have the same rights as a human being? This is a key issue in Frankenstein as well as in modern science fiction: for example, the film Artificial Intelligence: A.I. considers a machine in the form of a small boy which has been given the ability to feel human emotions, including, tragically, the capacity to suffer. Frankenstein or The Modern Prometheus, generally known as Frankenstein, is a Novel written by the British author Mary Shelley This issue is also being considered by futurists, such as California's Institute for the Future under the name "robot rights",^[22] although many critics believe that the discussion is premature. Futurists, or futurologists, are those who speculate about the future The Institute for the Future ( IFTF) is a Palo Alto California &ndashbased Think tank established in 1968 as a spin-off from the RAND Corporation This is a sub-article of Artificial intelligence (AI, describing the different futuristic portrayals of fictional artificial intelligence in books and film ^[23][24]

Science fiction writers and futurists have also speculated on the technology's potential impact on humanity. Futurists, or futurologists, are those who speculate about the future In fiction, AI has appeared as a servant (R2D2), a comrade (Lt. Commander Data), an extension to human abilities (Ghost in the Shell), a conqueror (The Matrix), a dictator (With Folded Hands) and an exterminator (Terminator, Battlestar Galactica). R2-D2 (called R2, or " Artoo " for short is a fictional character in the Star Wars universe, an Astromech droid Lieutenant Commander Data, played by actor Brent Spiner, is a character in the Star Trek Fictional universe. is a Japanese Cyberpunk Manga created by Masamune Shirow, and first published in 1989 in Young The Matrix is a 1999 science fiction - martial arts - Action film written and directed by Larry and Andy Wachowski and " With Folded Hands " is a 1947 Science fiction Novelette by Jack Williamson (1908-2006 The Terminator series is a franchise encompassing a series of Science fiction Films and ancillary media concerning battles between Skynet The Battlestar Galactica Science fiction franchise which began as a 1978 TV series, was "reimagined" in 2003 into a TV miniseries Some realistic potential consequences of AI are decreased human labor demand,^[25] the enhancement of human ability or experience,^[26] and a need for redefinition of human identity and basic values. ^[27]

Futurists estimate the capabilities of machines using Moore's Law, which measures the relentless exponential improvement in digital technology with uncanny accuracy. Futurists, or futurologists, are those who speculate about the future Moore's law describes an important trend in the History of computer hardware. Ray Kurzweil has calculated that desktop computers will have the same processing power as human brains by the year 2029, and that by 2045 artificial intelligence will reach a point where it is able to improve itself at a rate that far exceeds anything conceivable in the past, a scenario that science fiction writer Vernor Vinge named the "technological singularity". Raymond Kurzweil (kɚzwaɪl (born February 12 1948 is an inventor and Futurist. A desktop computer is a Personal computer (PC in a form intended for regular use at a single location as opposed to a mobile Laptop or portable computer Vernor Steffen Vinge (ˈvɪndʒi (born October 2, 1944 in Waukesha Wisconsin, U The technological singularity is a theoretical future point of unprecedented technological progress caused in part by the ability of machines to improve themselves using Artificial ^[28]

"Artificial intelligence is the next stage in evolution," Edward Fredkin said in the 1980s,^[29] expressing an idea first proposed by Samuel Butler's Darwin Among the Machines (1863), and expanded upon by George Dyson in his book of the same name (1998). Edward Fredkin (born 1934 is an early pioneer of Digital physics (in recent work he uses the term Digital philosophy (DP Samuel Butler ( December 4, 1835 - June 18, 1902 was an iconoclastic Victorian author who published a variety of works including the Darwin among the Machines appeared as the heading of an article published in The Press newspaper on 13 June 1863 in Christchurch, George Dyson (born 1953 is a scientific Historian, the son of Freeman Dyson, brother of Esther Dyson, and the grandson of Sir George Dyson Several futurists and science fiction writers have predicted that human beings and machines will merge in the future into cyborgs that are more capable and powerful than either. Futurists, or futurologists, are those who speculate about the future A cyborg is a Cybernetic Organism ( ie, an organism that has both artificial and natural systems This idea, called transhumanism, has roots in Aldous Huxley and Robert Ettinger, is now associated with robot designer Hans Moravec, cyberneticist Kevin Warwick and Ray Kurzweil. Transhumanism (sometimes symbolized by >H or H+) a term often used as a synonym for " Human enhancement " is an international intellectual Aldous Leonard Huxley (26 July 1894 &ndash 22 November 1963 was an English writer and one of the most prominent members of the famous Huxley family. Robert Chester Wilson Ettinger (born December 04, 1918) is known as "the father of Cryonics " due to the impact of his 1962 book See also Robot Robotics is the science and technology of Robots and their design manufacture and application Hans Moravec (born November 30 1948 in Austria) is a research Professor at the Robotics Institute (Carnegie Mellon of Carnegie Cybernetics is the interdisciplinary study of the Structure of Complex systems especially Communication processes control mechanisms and Feedback Kevin Warwick (born 9 February 1954 Coventry, UK is a British scientist and professor of Cybernetics at the University of Reading Raymond Kurzweil (kɚzwaɪl (born February 12 1948 is an inventor and Futurist. ^[28] Transhumanism has been illustrated in fiction as well, for example on the manga Ghost in the Shell

History of AI research

Main articles: history of artificial intelligence and timeline of artificial intelligence

In the middle of the 20th century, a handful of scientists began a new approach to building intelligent machines, based on recent discoveries in neurology, a new mathematical theory of information, an understanding of control and stability called cybernetics, and above all, by the invention of the digital computer, a machine based on the abstract essence of mathematical reasoning. Transhumanism (sometimes symbolized by >H or H+) a term often used as a synonym for " Human enhancement " is an international intellectual ˈmɑŋgə is the Japanese word for Comics (sometimes called komikku コミック and print Cartoons In their modern form manga date from shortly is a Japanese Cyberpunk Manga created by Masamune Shirow, and first published in 1989 in Young timeline of artificial intelligence The history of artificial intelligence begins in Antiquity with myths stories and rumors of artificial beings endowed with intelligence See also History of artificial intelligence To 1900 1900-1950 1950s 1960s 1970s Information as a concept has a diversity of meanings from everyday usage to technical settings Cybernetics is the interdisciplinary study of the Structure of Complex systems especially Communication processes control mechanisms and Feedback A computer is a Machine that manipulates data according to a list of instructions. ^[30]

The field of modern AI research was founded at conference on the campus of Dartmouth College in the summer of 1956. Dartmouth College ( is a private, Coeducational University located in Hanover, New Hampshire, U ^[31] Those who attended would become the leaders of AI research for many decades, especially John McCarthy, Marvin Minsky, Allen Newell and Herbert Simon, who founded AI laboratories at MIT, CMU and Stanford. John McCarthy (born September 4, 1927, in Boston, Massachusetts) is an American Computer scientist and Cognitive Marvin Lee Minsky (born August 9, 1927) is an American cognitive scientist in the field of Artificial intelligence (AI co-founder Allen Newell ( March 19, 1927 - July 19, 1992) was a researcher in Computer science and Cognitive psychology at the Herbert Alexander Simon ( June 15, 1916 February 9, 2001) was an American Political scientist whose research ranged Leland Stanford Junior University, commonly known as Stanford University or simply Stanford, is a private Research university located in They and their students wrote programs that were, to most people, simply astonishing:^[32] computers were solving word problems in algebra, proving logical theorems and speaking English. ^[33] By the middle 60s their research was heavily funded by the U.S. Department of Defense^[34] and they were optimistic about the future of the new field:

• 1965, H. A. Simon: "[M]achines will be capable, within twenty years, of doing any work a man can do"^[35]
• 1967, Marvin Minsky: "Within a generation . The Defense Advanced Research Projects Agency (DARPA is an agency of the United States Department of Defense responsible for the development of new Technology Herbert Alexander Simon ( June 15, 1916 February 9, 2001) was an American Political scientist whose research ranged Marvin Lee Minsky (born August 9, 1927) is an American cognitive scientist in the field of Artificial intelligence (AI co-founder . . the problem of creating 'artificial intelligence' will substantially be solved. "^[36]

These predictions, and many like them, would not come true. They had failed to recognize the difficulty of some of the problems they faced. ^[37] In 1974, in response to the criticism of England's Sir James Lighthill and ongoing pressure from Congress to fund more productive projects, the U. Sir Michael James Lighthill, FRS ( 23 January 1924 – 17 July 1998) was a British applied mathematician S. and British governments cut off all undirected, exploratory research in AI. This was the first AI Winter. See also History of artificial intelligence the first AI winter and the second AI winter An AI Winter is a collapse in the perception ^[38]

In the early 80s, AI research was revived by the commercial success of expert systems (a form of AI program that simulated the knowledge and analytical skills of one or more human experts) and by 1985 the market for AI had reached more than a billion dollars. An expert system is Software that attempts to reproduce the performance of one or more human Experts most commonly in a specific Problem domain, and is ^[39] Minsky and others warned the community that enthusiasm for AI had spiraled out of control and that disappointment was sure to follow. Marvin Lee Minsky (born August 9, 1927) is an American cognitive scientist in the field of Artificial intelligence (AI co-founder ^[40] Beginning with the collapse of the Lisp Machine market in 1987, AI once again fell into disrepute, and a second, more lasting AI Winter began. Lisp machines were general-purpose Computers designed (usually through hardware support to efficiently run Lisp as their main software language. See also History of artificial intelligence the first AI winter and the second AI winter An AI Winter is a collapse in the perception ^[41]

In the 90s and early 21st century AI achieved its greatest successes, albeit somewhat behind the scenes. Artificial intelligence was adopted throughout the technology industry, providing the heavy lifting for logistics, data mining, medical diagnosis and many other areas. Logistics is the management of the flow of Goods, Information and other resources including Energy and people between the point of origin and the point Data mining is the process of Sorting through large amounts of data and picking out relevant information Diagnosis is the identification by Process of elimination, of the nature of anything ^[42] The success was due to several factors: the incredible power of computers today (see Moore's law), a greater emphasis on solving specific subproblems, the creation of new ties between AI and other fields working on similar problems, and above all a new commitment by researchers to solid mathematical methods and rigorous scientific standards. Moore's law describes an important trend in the History of computer hardware. ^[43]

Philosophy of AI

Main article: philosophy of artificial intelligence

Can the brain be simulated by a digital computer? If it can, then would the simulation have a mind in the same sense that people do?

In a classic 1950 paper, Alan Turing posed the question "Can Machines Think?" In the years since, the philosophy of artificial intelligence has attempted to answer it. ethics of artificial intelligence The philosophy of artificial intelligence considers the relationship between machines and thought and attempts to answer such MIND ( Moving In New Directions) (est 1975 is an alternative education high school in Montreal, Quebec, Canada. Computing Machinery and Intelligence, written by Alan Turing and published in 1950 in Mind, is a seminal paper on the topic of Artificial Alan Mathison Turing, OBE, FRS (ˈt(jʊ(ərɪŋ (23 June 1912 &ndash 7 June 1954 was an English Mathematician ethics of artificial intelligence The philosophy of artificial intelligence considers the relationship between machines and thought and attempts to answer such ^[44]

• Turing's "polite convention": If a machine acts as intelligently as a human being, then it is as intelligent as a human being. The Turing test is a proposal for a test of a Machine 's ability to demonstrate intelligence Alan Turing theorized that, ultimately, we can only judge the intelligence of machine based on its behavior. Alan Mathison Turing, OBE, FRS (ˈt(jʊ(ərɪŋ (23 June 1912 &ndash 7 June 1954 was an English Mathematician This theory forms the basis of the Turing test. The Turing test is a proposal for a test of a Machine 's ability to demonstrate intelligence ^[45]
• The Dartmouth proposal: Every aspect of learning or any other feature of intelligence can be so precisely described that a machine can be made to simulate it. The Dartmouth Summer Research Conference on Artificial Intelligence was the name of a conference now considered the seminal event for Artificial intelligence as a This assertion was printed in the proposal for the Dartmouth Conference of 1956, and represents the position of most working AI researchers. The Dartmouth Summer Research Conference on Artificial Intelligence was the name of a conference now considered the seminal event for Artificial intelligence as a ^[46]
• Newell and Simon's physical symbol system hypothesis: A physical symbol system has the necessary and sufficient means of general intelligent action. Allen Newell ( March 19, 1927 - July 19, 1992) was a researcher in Computer science and Cognitive psychology at the Herbert Alexander Simon ( June 15, 1916 February 9, 2001) was an American Political scientist whose research ranged Philosophy of artificial intelligence A physical symbol system (also called a Formal system) takes physical patterns (symbols combining them into structures (expressions Philosophy of artificial intelligence A physical symbol system (also called a Formal system) takes physical patterns (symbols combining them into structures (expressions This statement claims that the essence of intelligence is symbol manipulation. ^[47] Hubert Dreyfus argued that, on the contrary, human expertise depends on unconscious instinct rather than conscious symbol manipulation and on having a "feel" for the situation rather than explicit symbolic knowledge. Hubert Lederer Dreyfus (born October 15, 1929 in Terre Haute Indiana to Stanley S ^[48]
• Gödel's incompleteness theorem: A physical symbol system can not prove all true statements. In Mathematical logic, Gödel's incompleteness theorems, proved by Kurt Gödel in 1931 are two Theorems stating inherent limitations of all but the most Philosophy of artificial intelligence A physical symbol system (also called a Formal system) takes physical patterns (symbols combining them into structures (expressions Roger Penrose is among those who claim that Gödel's theorem limits what machines can do. Sir Roger Penrose, PhD, OM, FRS (born 8 August 1931) is an English Mathematical physicist and Emeritus ^[49]
• Searle's "strong AI position": A physical symbol system can have a mind and mental states. John Rogers Searle (born July 31 1932 in Denver Colorado) is an American Philosopher and the Slusser Professor of Philosophy at the University Philosophy of artificial intelligence A physical symbol system (also called a Formal system) takes physical patterns (symbols combining them into structures (expressions MIND ( Moving In New Directions) (est 1975 is an alternative education high school in Montreal, Quebec, Canada. Consciousness has been defined loosely as a constellation of attributes of Mind such as Subjectivity, Self-awareness, Sentience, and the Searle counters this assertion with his Chinese room argument, which asks us to look inside the computer and try to find where the "mind" might be. Philosophy of artificial intelligence The Chinese Room argument comprises a Thought experiment and associated Arguments by John Searle, who attempts ^[50]
• The artificial brain argument: The brain can be simulated. Artificial brain is the research to develop software and hardware that has cognitive abilities similar to the animal or Human brain. Hans Moravec, Ray Kurzweil and others have argued that it is technologically feasible to copy the brain directly into hardware and software, and that such a simulation will be essentially identical to the original. Hans Moravec (born November 30 1948 in Austria) is a research Professor at the Robotics Institute (Carnegie Mellon of Carnegie Raymond Kurzweil (kɚzwaɪl (born February 12 1948 is an inventor and Futurist. This argument combines the idea that a suitably powerful machine can simulate any process, with the materialist idea that the mind is the result of a physical process in the brain. In computability theory, several closely-related terms are used to describe the "computational power" of a computational system (such as an Abstract machine or The Philosophy of materialism holds that the only thing that can be truly proven to exist is Matter, and is considered a form of Physicalism. MIND ( Moving In New Directions) (est 1975 is an alternative education high school in Montreal, Quebec, Canada. The brain is the center of the Nervous system in animals All Vertebrates and the majority of Invertebrates have a brain ^[51]

AI research

Problems of AI

While there is no universally accepted definition of intelligence,^[52] AI researchers have studied several traits that are considered essential. ^[6]

Deduction, reasoning, problem solving

Early AI researchers developed algorithms that imitated the process of conscious, step-by-step reasoning that human beings use when they solve puzzles, play board games, or make logical deductions. ^[53] By the late 80s and 90s, AI research had also developed highly successful methods for dealing with uncertain or incomplete information, employing concepts from probability and economics. Uncertainty is a term used in subtly different ways in a number of fields including Philosophy, Statistics, Economics, Finance, Insurance Probability is the likelihood or chance that something is the case or will happen Economics is the social science that studies the production distribution, and consumption of goods and services. ^[54]

For difficult problems, most of these algorithms can require enormous computational resources — most experience a "combinatorial explosion": the amount of memory or computer time required becomes astronomical when the problem goes beyond a certain size. In Mathematics a combinatorial explosion describes the effect of functions that grow very rapidly as a result of Combinatorial considerations The search for more efficient problem solving algorithms is a high priority for AI research. ^[55]

It is not clear, however, that conscious human reasoning is any more efficient when faced with a difficult abstract problem. Cognitive scientists have demonstrated that human beings solve most of their problems using unconscious reasoning, rather than the conscious, step-by-step deduction that early AI research was able to model. Cognitive science may be broadly defined as the multidisciplinary study of mind and behavior ^[56] Embodied cognitive science argues that unconscious sensorimotor skills are essential to our problem solving abilities. For approaches to Cognitive science that emphasize the Embodied mind see Embodied mind thesis Embodied Cognitive Science The Theory of Cognitive Development (one of the most historically influential theories was developed by Jean Piaget, a Swiss Philosopher (1896–1980 It is hoped that sub-symbolic methods, like computational intelligence and situated AI, will be able to model these instinctive skills. Computational intelligence (CI is an offshoot of Artificial intelligence. Nouvelle AI|behavior-based AI In Artificial intelligence and Cognitive science, the term situated refers to an agent which is Embedded in The problem of unconscious problem solving, which forms part of our commonsense reasoning, is largely unsolved. Commonsense reasoning is the branch of Artificial intelligence concerned with replicating human thinking

Knowledge representation

Main articles: knowledge representation and commonsense knowledge

Knowledge representation^[57] and knowledge engineering^[58] are central to AI research. Knowledge representation is an area in Artificial intelligence that is concerned with how to formally "think" that is how to use a symbol system to represent In Artificial intelligence research commonsense knowledge is the collection of facts and information that an ordinary person is expected to know Knowledge representation is an area in Artificial intelligence that is concerned with how to formally "think" that is how to use a symbol system to represent Knowledge engineering (KE has been defined by Feigenbaum and McCorduck (1983 as follows ""KE is an engineering discipline that involves integrating knowledge into Many of the problems machines are expected to solve will require extensive knowledge about the world. Among the things that AI needs to represent are: objects, properties, categories and relations between objects;^[59] situations, events, states and time;^[60] causes and effects;^[61] knowledge about knowledge (what we know about what other people know);^[62] and many other, less well researched domains. A complete representation of "what exists" is an ontology^[63] (borrowing a word from traditional philosophy), of which the most general are called upper ontologies. An ontology in both Computer science and Information science is a formal representation of a set of concepts within a domain and the relationships between Philosophy is the study of general problems concerning matters such as existence knowledge truth beauty justice validity mind and language In Information science, an upper ontology ( top-level ontology, or foundation ontology) is an attempt to create an ontology which describes very

Among the most difficult problems in knowledge representation are:

• Default reasoning and the qualification problem: Many of the things people know take the form of "working assumptions. In Philosophy and AI (especially knowledge based systems the qualification problem is concerned with the impossibility of listing all the Preconditions " For example, if a bird comes up in conversation, people typically picture an animal that is fist sized, sings, and flies. None of these things are true about birds in general. John McCarthy identified this problem in 1969^[64] as the qualification problem: for any commonsense rule that AI researchers care to represent, there tend to be a huge number of exceptions. John McCarthy (born September 4, 1927, in Boston, Massachusetts) is an American Computer scientist and Cognitive Almost nothing is simply true or false in the way that abstract logic requires. AI research has explored a number of solutions to this problem. ^[65]
• Unconscious knowledge: Much of what people know isn't represented as "facts" or "statements" that they could actually say out loud. They take the form of intuitions or tendencies and are represented in the brain unconsciously and sub-symbolically. This unconscious knowledge informs, supports and provides a context for our conscious knowledge. As with the related problem of unconscious reasoning, it is hoped that situated AI or computational intelligence will provide ways to represent this kind of knowledge. Nouvelle AI|behavior-based AI In Artificial intelligence and Cognitive science, the term situated refers to an agent which is Embedded in Computational intelligence (CI is an offshoot of Artificial intelligence.
• The breadth of common sense knowledge: The number of atomic facts that the average person knows is astronomical. In Artificial intelligence research commonsense knowledge is the collection of facts and information that an ordinary person is expected to know Research projects that attempt to build a complete knowledge base of commonsense knowledge, such as Cyc, require enormous amounts of tedious step-by-step ontological engineering — they must be built, by hand, one complicated concept at a time. In Artificial intelligence research commonsense knowledge is the collection of facts and information that an ordinary person is expected to know Cyc is an artificial intelligence project that attempts to assemble a comprehensive ontology and Database of everyday Common sense knowledge, ^[66]

Planning

Main article: automated planning and scheduling

Intelligent agents must be able to set goals and achieve them. Automated planning and scheduling is a branch of Artificial intelligence that concerns the realisation of strategies or action sequences typically for execution by ^[67] They need a way to visualize the future: they must have a representation of the state of the world and be able to make predictions about how their actions will change it. They must also attempt to determine the utility or "value" of the choices available to it. In Economics, utility is a measure of the relative satisfaction from or desirability of Consumption of various Goods and services. ^[68]

In some planning problems, the agent can assume that it is the only thing acting on the world and it can be certain what the consequences of its actions may be. ^[69] However, if this is not true, it must periodically check if the world matches its predictions and it must change its plan as this becomes necessary, requiring the agent to reason under uncertainty. ^[70]

Multi-agent planning tries to determine the best plan for a community of agents, using cooperation and competition to achieve a given goal. In Computer science multi-agent planning involves coordinating the resources and activities of multiple " agents " Distinguish from Corporation. Cooperation, co-operation, or coöperation is the process of working or acting together Competition is a rivalry between individuals groups nations or animals for territory or resources Emergent behavior such as this is used by both evolutionary algorithms and swarm intelligence. For other uses see Emergence (disambiguation, Emergent, and Emergency. In Artificial intelligence, an evolutionary algorithm (EA is a Subset of Evolutionary computation, a generic population-based Metaheuristic Swarm intelligence (SI is Artificial intelligence based on the Collective behavior of decentralized, self-organized systems ^[71]

Learning

Main article: machine learning

Important machine learning^[72] problems are:

• Unsupervised learning: find a model that matches a stream of input "experiences", and be able to predict what new "experiences" to expect. Machine learning is a subfield of Artificial intelligence that is concerned with the design and development of Algorithms and techniques that allow computers to "learn" Machine learning is a subfield of Artificial intelligence that is concerned with the design and development of Algorithms and techniques that allow computers to "learn" In Machine learning, unsupervised learning is a class of problems in which one seeks to determine how the data are organised
• Supervised learning, such as classification (be able to determine what category something belongs in, after seeing a number of examples of things from each category), or regression (given a set of numerical input/output examples, discover a continuous function that would generate the outputs from the inputs). Supervised learning is a Machine learning technique for learning a function from training data Statistical classification is a procedure in which individual items are placed into groups based on quantitative information on one or more characteristics inherent in the items (referred
• Reinforcement learning:^[73] the agent is rewarded for good responses and punished for bad ones. Inspired by related psychological theory in Computer science, reinforcement learning is a sub-area of Machine learning concerned with how an agent (These can be analyzed in terms decision theory, using concepts like utility). Decision theory in Mathematics and Statistics is concerned with identifying the Values uncertainties and other issues relevant in a given In Economics, utility is a measure of the relative satisfaction from or desirability of Consumption of various Goods and services.

Natural language processing

Main article: natural language processing

Natural language processing^[74] gives machines the ability to read and understand the languages human beings speak. Natural language processing ( NLP) is a subfield of Artificial intelligence and Computational linguistics. Natural language processing ( NLP) is a subfield of Artificial intelligence and Computational linguistics. Many researchers hope that a sufficiently powerful natural language processing system would be able to acquire knowledge on its own, by reading the existing text available over the internet. Some straightforward applications of natural language processing include information retrieval (or text mining) and machine translation. Information retrieval ( IR) is the science of searching for documents for Information within documents and for metadata about documents as well as that Text mining, sometimes alternately referred to as text Data mining, roughly equivalent to Text analytics, refers generally to the process Machine translation, sometimes referred to by the abbreviation ^[75]

Motion and manipulation

ASIMO uses sensors and intelligent algorithms to avoid obstacles and navigate stairs. is a Humanoid robot created by Honda Motor Company. Standing at 130 Centimeters (4 feet 3 Inches) and weighing 54 Kilograms (119

Main article: robotics

The field of robotics^[76] is closely related to AI. See also Robot Robotics is the science and technology of Robots and their design manufacture and application See also Robot Robotics is the science and technology of Robots and their design manufacture and application Intelligence is required for robots to be able to handle such tasks as object manipulation^[77] and navigation, with sub-problems of localization (knowing where you are), mapping (learning what is around you) and motion planning (figuring out how to get there). Motion planning (aka the "navigation problem" the "piano mover's problem" is a term used in Robotics for the process of detailing a task into atomic The problem of Robotic mapping is related to Cartography.The goal is for an Autonomous robot to be able to construct (or use) a map or Floor plan Motion planning (aka the "navigation problem" the "piano mover's problem" is a term used in Robotics for the process of detailing a task into atomic ^[78]

Perception

Main articles: machine perception, computer vision, and speech recognition

Machine perception^[79] is the ability to use input from sensors (such as cameras, microphones, sonar and others more exotic) to deduce aspects of the world. In Computing, machine perception is the ability of computing machines to sense and interpret images sounds or other contents of their environments or of the contents of stored Computer vision is the science and technology of machines that see Speech recognition (also known as automatic speech recognition or computer speech recognition) converts spoken words to machine-readable input (for example to keypresses In Computing, machine perception is the ability of computing machines to sense and interpret images sounds or other contents of their environments or of the contents of stored Computer vision^[80] is the ability to analyze visual input. Computer vision is the science and technology of machines that see A few selected subproblems are speech recognition,^[81] facial recognition and object recognition. Speech recognition (also known as automatic speech recognition or computer speech recognition) converts spoken words to machine-readable input (for example to keypresses Object recognition in Computer vision is a task of finding given object in an image or video sequence ^[82]

Social intelligence

Main article: affective computing

Kismet, a robot with rudimentary social skills. Affective Computing is also the title of a textbook on the subject by Rosalind Picard. Kismet is a Robot made in the late 1990s at MIT with auditory visual and expressive systems intended to participate in human social interaction and to demonstrate

Emotion and social skills play two roles for an intelligent agent:^[83]

• It must be able to predict the actions of others, by understanding their motives and emotional states. (This involves elements of game theory, decision theory, as well as the ability to model human emotions and the perceptual skills to detect emotions. Game theory is a branch of Applied mathematics that is used in the Social sciences (most notably Economics) Biology, Engineering, Decision theory in Mathematics and Statistics is concerned with identifying the Values uncertainties and other issues relevant in a given )
• For good human-computer interaction, an intelligent machine also needs to display emotions — at the very least it must appear polite and sensitive to the humans it interacts with. Human–computer interaction or HCI is the study of interaction between people ( users and Computers It is often regarded as the intersection of At best, it should appear to have normal emotions itself.

Creativity

Main article: Computational creativity

A sub-field of AI addresses creativity both theoretically (from a philosophical and psychological perspective) and practically (via specific implementations of systems that generate outputs that can be considered creative). Computational creativity (also known as artificial creativity, mechanical creativity or creative computation) is a multidisciplinary endeavour that is located Creativity is a mental process involving the generation of new Ideas or Concepts, or new associations of the creative mind between existing ideas or concepts

General intelligence

Main articles: strong AI and AI-complete

Most researchers hope that their work will eventually be incorporated into a machine with general intelligence (known as strong AI), combining all the skills above and exceeding human abilities at most or all of them. Strong AI is Artificial intelligence that matches or exceeds human intelligence —the intelligence of a machine that can successfully perform any intellectual task In the field of Artificial intelligence, the most difficult problems are informally known as AI-complete or AI-hard, implying that the difficulty of these computational Strong AI is Artificial intelligence that matches or exceeds human intelligence —the intelligence of a machine that can successfully perform any intellectual task ^[7] A few believe that anthropomorphic features like artificial consciousness or an artificial brain may be required for such a project. Anthropomorphism is the attribution of uniquely Human characteristics to non-human creatures and beings natural and supernatural phenomena material states and objects strong AI Artificial consciousness (AC also known as machine consciousness (MC or synthetic consciousness, is a field related to Artificial intelligence Artificial brain is the research to develop software and hardware that has cognitive abilities similar to the animal or Human brain.

Many of the problems above are considered AI-complete: to solve one problem, you must solve them all. In the field of Artificial intelligence, the most difficult problems are informally known as AI-complete or AI-hard, implying that the difficulty of these computational For example, even a straightforward, specific task like machine translation requires that the machine follow the author's argument (reason), know what it's talking about (knowledge), and faithfully reproduce the author's intention (social intelligence). Machine translation, sometimes referred to by the abbreviation Machine translation, therefore, is believed to be AI-complete: it may require strong AI to be done as well as humans can do it. Machine translation, sometimes referred to by the abbreviation Strong AI is Artificial intelligence that matches or exceeds human intelligence —the intelligence of a machine that can successfully perform any intellectual task ^[84]

Approaches to AI

There are as many approaches to AI as there are AI researchers—any coarse categorization is likely to be unfair to someone. Artificial intelligence communities have grown up around particular problems, institutions and researchers, as well as the theoretical insights that define the approaches described below. Artificial intelligence is a young science and is still a fragmented collection of subfields. At present, there is no established unifying theory that links the subfields into a coherent whole.

Cybernetics and brain simulation

In the 40s and 50s, a number of researchers explored the connection between neurology, information theory, and cybernetics. Information theory is a branch of Applied mathematics and Electrical engineering involving the quantification of Information. Cybernetics is the interdisciplinary study of the Structure of Complex systems especially Communication processes control mechanisms and Feedback Some of them built machines that used electronic networks to exhibit rudimentary intelligence, such as W. Grey Walter's turtles and the Johns Hopkins Beast. W Grey Walter ( February 19 1910 &ndash May 6 1977) was a Neurophysiologist and Robotician. Turtles are a class of educational Robots designed originally in the late 1940s (largely under the auspices of researcher William Grey Walter) and used in Computer The Johns Hopkins Beast was an early Robot built in the 1960 at Johns Hopkins University. Many of these researchers gathered for meetings of the Teleological Society at Princeton and the Ratio Club in England. The Ratio Club was a small informal Dining club of young psychologists, physiologists, mathematicians and engineers who met to discuss ^[85]

Traditional symbolic AI

When access to digital computers became possible in the middle 1950s, AI research began to explore the possibility that human intelligence could be reduced to symbol manipulation. The research was centered in three institutions: CMU, Stanford and MIT, and each one developed its own style of research. Carnegie Mellon University (also known as CMU) is a private Research University in Pittsburgh, Pennsylvania, United Leland Stanford Junior University, commonly known as Stanford University or simply Stanford, is a private Research university located in John Haugeland named these approaches to AI "good old fashioned AI" or "GOFAI". John Haugeland (born in 1945 is a professor of Philosophy at the University of Chicago, where he chairs the GOFAI stands for "Good Old-Fashioned Artificial Intelligence". ^[86]

Cognitive simulation

Economist Herbert Simon and Alan Newell studied human problem solving skills and attempted to formalize them, and their work laid the foundations of the field of artificial intelligence, as well as cognitive science, operations research and management science. An economist is an expert in the Social science of Economics. Herbert Alexander Simon ( June 15, 1916 February 9, 2001) was an American Political scientist whose research ranged Allen Newell ( March 19, 1927 - July 19, 1992) was a researcher in Computer science and Cognitive psychology at the Cognitive science may be broadly defined as the multidisciplinary study of mind and behavior Operations Research (OR in North America South Africa and Australia and Operational Research in Europe is an interdisciplinary branch of applied Mathematics and Management science (MS, is the discipline of using Mathematical modeling and other analytical methods to help make better business Management decisions Their research team performed psychological experiments to demonstrate the similarities between human problem solving and the programs (such as their "General Problem Solver") they were developing. Psychology (from Greek grc ψῡχή psȳkhē, "breath life soul" and grc -λογία -logia) is an Academic and General Problem Solver ( GPS) was a Computer program created in 1957 by Herbert Simon and Allen Newell to build a universal problem This tradition, centered at Carnegie Mellon University,^[87] would eventually culminate in the development of the Soar architecture in the middle 80s. Carnegie Mellon University (also known as CMU) is a private Research University in Pittsburgh, Pennsylvania, United Soar (originally known as SOAR) is a symbolic Cognitive architecture, created by John Laird, Allen Newell, and Paul Rosenbloom at ^[88]

Logical AI

Unlike Newell and Simon, John McCarthy felt that machines did not need to simulate human thought, but should instead try to find the essence of abstract reasoning and problem solving, regardless of whether people used the same algorithms. Allen Newell ( March 19, 1927 - July 19, 1992) was a researcher in Computer science and Cognitive psychology at the Herbert Alexander Simon ( June 15, 1916 February 9, 2001) was an American Political scientist whose research ranged John McCarthy (born September 4, 1927, in Boston, Massachusetts) is an American Computer scientist and Cognitive ^[89] His laboratory at Stanford (SAIL) focused on using formal logic to solve a wide variety of problems, including knowledge representation, planning and learning. Leland Stanford Junior University, commonly known as Stanford University or simply Stanford, is a private Research university located in The Stanford Artificial Intelligence Laboratory (also known as Stanford AI Lab or SAIL) is the Artificial intelligence (AI research laboratory of Logic is the study of the principles of valid demonstration and Inference. Knowledge representation is an area in Artificial intelligence that is concerned with how to formally "think" that is how to use a symbol system to represent Automated planning and scheduling is a branch of Artificial intelligence that concerns the realisation of strategies or action sequences typically for execution by Machine learning is a subfield of Artificial intelligence that is concerned with the design and development of Algorithms and techniques that allow computers to "learn" Work in logic led to the development of the programming language Prolog and the science of logic programming. Prolog is a Logic programming language It is a general purpose language often associated with Artificial intelligence and Computational linguistics Logic programming is in its broadest sense the use of mathematical logic for computer programming ^[90]

"Scruffy" symbolic AI

Researchers at MIT (such as Marvin Minsky and Seymour Papert) found that solving difficult problems in vision and natural language processing required ad-hoc solutions – they argued that there was no easy answer, no simple and general principle (like logic) that would capture all the aspects of intelligent behavior. Marvin Lee Minsky (born August 9, 1927) is an American cognitive scientist in the field of Artificial intelligence (AI co-founder Seymour Papert (born February 29, 1928 in Pretoria South Africa) is an MIT Mathematician, computer scientist, and Computer vision is the science and technology of machines that see Natural language processing ( NLP) is a subfield of Artificial intelligence and Computational linguistics. The Metaphor of the Silver Bullet applies to any straightforward solution perceived to have extreme effectiveness Logic is the study of the principles of valid demonstration and Inference. Roger Schank described their "anti-logic" approaches as "scruffy" (as opposed to the "neat" paradigms at CMU and Stanford),^[91] and this still forms the basis of research into commonsense knowledge bases (such as Doug Lenat's Cyc) which must be built one complicated concept at a time. Roger Schank (* 1946 is president and CEO of Socratic Arts, and a leading visionary in Artificial intelligence. In Artificial intelligence, the labels neats and scruffies are used to refer to one of the continuing philosophical disputes in artificial intelligence research In Artificial intelligence, the labels neats and scruffies are used to refer to one of the continuing philosophical disputes in artificial intelligence research Leland Stanford Junior University, commonly known as Stanford University or simply Stanford, is a private Research university located in In Artificial intelligence research commonsense knowledge is the collection of facts and information that an ordinary person is expected to know Douglas B Lenat (born in 1950 is the CEO of Cycorp Inc of Austin Texas, and has been a prominent researcher in Artificial intelligence, Cyc is an artificial intelligence project that attempts to assemble a comprehensive ontology and Database of everyday Common sense knowledge,

Knowledge based AI

When computers with large memories became available around 1970, researchers from all three traditions began to build knowledge into AI applications. Knowledge representation is an area in Artificial intelligence that is concerned with how to formally "think" that is how to use a symbol system to represent This "knowledge revolution" led to the development and deployment of expert systems (introduced by Edward Feigenbaum), the first truly successful form of AI software. An expert system is Software that attempts to reproduce the performance of one or more human Experts most commonly in a specific Problem domain, and is Edward Albert Feigenbaum (born January 20 1936; Weehawken, US ^[92] The knowledge revolution was also driven by the realization that truly enormous amounts of knowledge would be required by many simple AI applications.

Sub-symbolic AI

During the 1960s, symbolic approaches had achieved great success at simulating high-level thinking in small demonstration programs. Approaches based on cybernetics or neural networks were abandoned or pushed into the background. Cybernetics is the interdisciplinary study of the Structure of Complex systems especially Communication processes control mechanisms and Feedback Traditionally the term neural network had been used to refer to a network or circuit of biological neurons. ^[93] By the 1980s, however, progress in symbolic AI seemed to stall and many believed that symbolic systems would never be able to imitate all the processes of human cognition, especially perception, robotics, learning and pattern recognition. In Computing, machine perception is the ability of computing machines to sense and interpret images sounds or other contents of their environments or of the contents of stored See also Robot Robotics is the science and technology of Robots and their design manufacture and application Machine learning is a subfield of Artificial intelligence that is concerned with the design and development of Algorithms and techniques that allow computers to "learn" Pattern recognition is a sub-topic of Machine learning. It is "the act of taking in raw data and taking an action based on the category of the data" A number of researchers began to look into "sub-symbolic" approaches to specific AI problems. ^[94]

Bottom-up, situated, behavior based or nouvelle AI

Researchers from the related field of robotics, such as Rodney Brooks, rejected symbolic AI and focussed on the basic engineering problems that would allow robots to move and survive. See also Robot Robotics is the science and technology of Robots and their design manufacture and application Rodney Allen Brooks (b December 30, 1954, in Adelaide, Australia) is Panasonic Professor of Robotics at the Massachusetts Institute ^[95] Their work revived the non-symbolic viewpoint of the early cybernetics researchers of the 50s and reintroduced the use of control theory in AI. Cybernetics is the interdisciplinary study of the Structure of Complex systems especially Communication processes control mechanisms and Feedback Control theory is an interdisciplinary branch of Engineering and Mathematics, that deals with the behavior of Dynamical systems The desired output These approaches are also conceptually related to the embodied mind thesis. Embodiment Philosophers cognitive scientists and artificial intelligence researchers who study embodied cognition and the embodied mind argue

Computational Intelligence

Interest in neural networks and "connectionism" was revived by David Rumelhart and others in the middle 1980s. Traditionally the term neural network had been used to refer to a network or circuit of biological neurons. Connectionism is an approach in the fields of Artificial intelligence, Cognitive psychology / Cognitive science, Neuroscience and Philosophy David Everett Rumelhart (b 1942, Wessington Springs, South Dakota) has made many contributions to the formal analysis of Human cognition, working ^[96] These and other sub-symbolic approaches, such as fuzzy systems and evolutionary computation, are now studied collectively by the emerging discipline of computational intelligence. A fuzzy control system is a control system based on Fuzzy logic - a mathematical system that analyzes analog input values in terms of logical variables In Computer science evolutionary computation is a subfield of Artificial intelligence (more particularly Computational intelligence) that involves Computational intelligence (CI is an offshoot of Artificial intelligence. ^[97]

The new neats

In the 1990s, AI researchers developed sophisticated mathematical tools to solve specific subproblems. These tools are truly scientific, in the sense that their results are both measurable and verifiable, and they have been responsible for many of AI's recent successes. Scientific method refers to bodies of Techniques for investigating phenomena The shared mathematical language has also permitted a high level of collaboration with more established fields (like mathematics, economics or operations research). Mathematics is the body of Knowledge and Academic discipline that studies such concepts as Quantity, Structure, Space and Economics is the social science that studies the production distribution, and consumption of goods and services. Operations Research (OR in North America South Africa and Australia and Operational Research in Europe is an interdisciplinary branch of applied Mathematics and Russell & Norvig (2003) describe this movement as nothing less than a "revolution" and "the victory of the neats. In Artificial intelligence, the labels neats and scruffies are used to refer to one of the continuing philosophical disputes in artificial intelligence research "^[98]

Intelligent agent paradigm

The "intelligent agent" paradigm became widely accepted during the 1990s. In Artificial intelligence, an intelligent agent ( IA) is an entity which observes "reason" and acts upon an environment (i ^[99][100] Although earlier researchers had proposed modular "divide and conquer" approaches to AI,^[101] the intelligent agent did not reach its modern form until Judea Pearl, Alan Newell and others brought concepts from decision theory and economics into the study of AI. In Artificial intelligence, an intelligent agent ( IA) is an entity which observes "reason" and acts upon an environment (i Judea Pearl is a Computer scientist and Philosopher, best known for developing the probabilistic approach to Artificial intelligence, in Allen Newell ( March 19, 1927 - July 19, 1992) was a researcher in Computer science and Cognitive psychology at the Decision theory in Mathematics and Statistics is concerned with identifying the Values uncertainties and other issues relevant in a given Economics is the social science that studies the production distribution, and consumption of goods and services. ^[102] When the economist's definition of a rational agent was married to computer science's definition of an object or module, the intelligent agent paradigm was complete. Economics is the social science that studies the production distribution, and consumption of goods and services. In Economics, an agent is an actor in a model that (generally solves an optimization problem Computer science (or computing science) is the study and the Science of the theoretical foundations of Information and Computation and their Object-oriented programming (OOP is a Programming paradigm that uses " objects " and their interactions to design applications and computer programs Modular programming is a software design technique that increases the extent to which software is composed from separate parts called modules In Artificial intelligence, an intelligent agent ( IA) is an entity which observes "reason" and acts upon an environment (i

An intelligent agent is a system that perceives its environment and takes actions which maximizes its chances of success. In Artificial intelligence, an intelligent agent ( IA) is an entity which observes "reason" and acts upon an environment (i The simplest intelligent agents are programs that solve specific problems. The most complicated intelligent agents would be rational, thinking human beings. ^[100]

The paradigm gives researchers license to study isolated problems and find solutions that are both verifiable and useful, without agreeing on one single approach. An agent that solves a specific problem can use any approach that works — some agents are symbolic and logical, some are sub-symbolic neural networks and some can be based on new approaches (without forcing researchers to reject old approaches that have proven useful). Traditionally the term neural network had been used to refer to a network or circuit of biological neurons. The paradigm gives researchers a common language to describe problems and share their solutions with each other and with other fields—such as decision theory—that also use concepts of abstract agents. Decision theory in Mathematics and Statistics is concerned with identifying the Values uncertainties and other issues relevant in a given

Integrating the approaches

An agent architecture or cognitive architecture allows researchers to build more versatile and intelligent systems out of interacting intelligent agents in a multi-agent system. In Computer science, agent architecture is a Blueprint for Software agents and Intelligent control systems depicting the arrangement of components A cognitive architecture is a blueprint for Intelligent agents It proposes (artificial Computational processes that act like certain cognitive systems most often In Artificial intelligence, an intelligent agent ( IA) is an entity which observes "reason" and acts upon an environment (i A multi-agent system ( MAS) is a system composed of multiple interacting Intelligent agents Multi-agent systems can be used to solve problems which are difficult or ^[103] A system with both symbolic and sub-symbolic components is a hybrid intelligent system, and the study of such systems is artificial intelligence systems integration. Hybrid intelligent system denotes a software system which employs in parallel a combination of methods and techniques from artificial intelligence subfields as Neuro-fuzzy The core idea of AI systems integration is making individual Software components such as Speech synthesizers interoperable with other components such as common A hierarchical control system provides a bridge between sub-symbolic AI at its lowest, reactive levels and traditional symbolic AI at its highest levels, where relaxed time constraints permit planning and world modelling. A Hierarchical control system is a form of Control System in which a set of devices and governing software is arranged in a Hierarchical tree. ^[104] Rodney Brooks' subsumption architecture was an early proposal for such a hierarchical system. Rodney Allen Brooks (b December 30, 1954, in Adelaide, Australia) is Panasonic Professor of Robotics at the Massachusetts Institute Subsumption architecture is a reactive robot architecture heavily associated with Behavior-based robotics.

Tools of AI research

In the course of 50 years of research, AI has developed a large number of tools to solve the most difficult problems in computer science. Computer science (or computing science) is the study and the Science of the theoretical foundations of Information and Computation and their A few of the most general of these methods are discussed below.

Search

Main article: search algorithm

Many problems in AI can be solved in theory by intelligently searching through many possible solutions:^[105] Reasoning can be reduced to performing a search. In Computer science, a search algorithm, broadly speaking is an Algorithm that takes a problem as Input and returns a solution to the problem usually For example, logical proof can be viewed as searching for a path that leads from premises to conclusions, where each step is the application of an inference rule. In Discourse and Logic, a premise is a claim that is a reason (or element of a set of reasons for or objection against some other claim A conclusion is a Proposition, which is arrived at after the consideration of Evidence, Arguments or Premises Logic In Logic, a rule of inference (also called a transformation rule) is a function from sets of formulae to formulae ^[106] Planning algorithms search through trees of goals and subgoals, attempting to find a path to a target goal. Automated planning and scheduling is a branch of Artificial intelligence that concerns the realisation of strategies or action sequences typically for execution by ^[107] Robotics algorithms for moving limbs and grasping objects use local searches in configuration space. See also Robot Robotics is the science and technology of Robots and their design manufacture and application In Computer science, local search is a Metaheuristic for solving computationally hard optimization problems "Configuration space" may also refer to PCI Configuration Space. ^[77] Many learning algorithms have search at their core. Machine learning is a subfield of Artificial intelligence that is concerned with the design and development of Algorithms and techniques that allow computers to "learn" ^[108]

There are several types of search algorithms:

• "Uninformed" search algorithms eventually search through every possible answer until they locate their goal. ^[109] Naive algorithms quickly run into problems when they expand the size of their search space to astronomical numbers. Astronomy (from the Greek words astron (ἄστρον "star" and nomos (νόμος "law" is the scientific study The result is a search that is too slow or never completes. In Computational complexity theory, computation time is a measure of how many steps are used by some Abstract machine in a particular computation
• Heuristic or "informed" searches use heuristic methods to eliminate choices that are unlikely to lead to their goal, thus drastically reducing the number of possibilities they must explore. heuristic (hyu̇-ˈris-tik is a method to help solve a problem commonly an informal method ^[110] The eliminatation of choices that are certain not to lead to the goal is called pruning. Pruning is a term in Mathematics and Informatics which describes a method of Enumeration, which allows to cut parts of a Decision tree.
• Local searches, such as hill climbing, simulated annealing and beam search, use techniques borrowed from optimization theory. In Computer science, local search is a Metaheuristic for solving computationally hard optimization problems In Computer science, hill climbing is a mathematical optimization technique which belongs to the family of local search. Simulated annealing (SA is a generic probabilistic Meta-algorithm for the Global optimization problem namely locating a good approximation to the In Mathematics, the term optimization, or mathematical programming, refers to the study of problems in which one seeks to minimize or maximize a real function ^[111]
• Global searches are more robust in the presence of local optima. Global optimization is a branch of Applied mathematics and Numerical analysis that deals with the optimization of a function or a set Local optimum is a term in Applied mathematics and Computer science. Techniques include evolutionary algorithms, swarm intelligence and random optimization algorithms. In Artificial intelligence, an evolutionary algorithm (EA is a Subset of Evolutionary computation, a generic population-based Metaheuristic Swarm intelligence (SI is Artificial intelligence based on the Collective behavior of decentralized, self-organized systems Random optimization is the name applied to a class of Algorithms which can be used to solve optimization problems

Logic

Main article: logic programming

Logic^[112] was introduced into AI research by John McCarthy in his 1958 Advice Taker proposal. Logic programming is in its broadest sense the use of mathematical logic for computer programming Logic is the study of the principles of valid demonstration and Inference. John McCarthy (born September 4, 1927, in Boston, Massachusetts) is an American Computer scientist and Cognitive The advice taker was a hypothetical Computer program, proposed by John McCarthy in his 1958 paper "Programs with Common Sense". The most important technical development was J. Alan Robinson's discovery of the resolution and unification algorithm for logical deduction in 1963. In Mathematical logic and Automated theorem proving, resolution is a rule of Inference leading to a refutation Theorem-proving technique In Mathematical logic, in particular as applied to Computer science, a unification of two terms is a join (in the lattice sense with respect This procedure is simple, complete and entirely algorithmic, and can easily be performed by digital computers. ^[113] However, a naive implementation of the algorithm quickly leads to a combinatorial explosion or an infinite loop. In Mathematics a combinatorial explosion describes the effect of functions that grow very rapidly as a result of Combinatorial considerations An infinite loop is a sequence of instructions in a computer program which loops endlessly either due to the loop having no terminating condition or having one that can In 1974, Robert Kowalski suggested representing logical expressions as Horn clauses (statements in the form of rules: "if p then q"), which reduced logical deduction to backward chaining or forward chaining. Robert "Bob" Anthony Kowalski (born May 15, 1941, in Bridgeport, Connecticut, U In Mathematical logic, a Horn clause is a clause (a Disjunction of literals with at most one positive literal Backward chaining (or backward reasoning) is an inference method used in Artificial intelligence. Forward chaining is one of the two main methods of reasoning when using Inference rules (in Artificial intelligence) This greatly alleviated (but did not eliminate) the problem. ^[106][114]

Logic is used for knowledge representation and problem solving, but it can be applied to other problems as well. For example, the satplan algorithm uses logic for planning,^[115] and inductive logic programming is a method for learning. Satplan is a method for Automated planning. It converts the planning problem instance into an instance of the Boolean satisfiability problem, which is then solved Automated planning and scheduling is a branch of Artificial intelligence that concerns the realisation of strategies or action sequences typically for execution by Inductive logic programming ( ILP) is a subfield of Machine learning which uses Logic programming as a uniform representation for examples background knowledge Machine learning is a subfield of Artificial intelligence that is concerned with the design and development of Algorithms and techniques that allow computers to "learn" ^[116]

There are several different forms of logic used in AI research.

• Propositional logic^[117] or sentential logic is the logic of statements which can be true or false. This is a technical mathematical article about the area of mathematical logic variously known as "propositional calculus" or "propositional logic" This is a technical mathematical article about the area of mathematical logic variously known as "propositional calculus" or "propositional logic"

• First-order logic^[118] also allows the use of quantifiers and predicates, and can express facts about objects, their properties, and their relations with each other. First-order logic (FOL is a formal Deductive system used in mathematics philosophy linguistics and computer science Quantification has two distinct meanings In Mathematics and Empirical science, it refers to human acts known as Counting and Measuring

• Fuzzy logic, a version of first-order logic which allows the truth of a statement to be represented as a value between 0 and 1, rather than simply True (1) or False (0). Fuzzy logic is a form of Multi-valued logic derived from Fuzzy set theory to deal with Reasoning that is approximate rather than precise Fuzzy systems can be used for uncertain reasoning and have been widely used in modern industrial and consumer product control systems. A fuzzy control system is a control system based on Fuzzy logic - a mathematical system that analyzes analog input values in terms of logical variables ^[119]

• Default logics, non-monotonic logics and circumscription are forms of logic designed to help with default reasoning and the qualification problem. Default logic is a Non-monotonic logic proposed by Raymond Reiter to formalize reasoning with default assumptions A non-monotonic logic is a Formal logic whose consequence relation is not monotonic. In Philosophy and AI (especially knowledge based systems the qualification problem is concerned with the impossibility of listing all the Preconditions ^[65]
• Several extensions of logic have been designed to handle specific domains of knowledge, such as: description logics;^[59] situation calculus, event calculus and fluent calculus (for representing events and time);^[60] causal calculus;^[61] belief calculus; and modal logics. Knowledge representation is an area in Artificial intelligence that is concerned with how to formally "think" that is how to use a symbol system to represent Description logics (DL are a family of Knowledge representation languages which can be used to represent the concept definitions of an application domain (known as terminological The situation calculus is a Logic formalism designed for representing and reasoning about dynamical domains The event calculus is a Logical language for representing and reasoning about actions and their effects first presented by Robert Kowalski and Marek Sergot in The fluent calculus is a formalism for expressing dynamical domains in First-order logic. Causality (but not causation) denotes a necessary relationship between one event (called cause and another event (called effect) which is the direct consequence A modal logic is any system of formal logic that attempts to deal with modalities. ^[62]

Probabilistic methods for uncertain reasoning

Main articles: Bayesian network, hidden Markov model, Kalman filter, decision theory, and utility theory

Many problems in AI (in reasoning, planning, learning, perception and robotics) require the agent to operate with incomplete or uncertain information. A Bayesian network (or a belief network) is a Probabilistic graphical model that represents a set of Variables and their probabilistic independencies A hidden Markov model ( HMM) is a Statistical model in which the system being modeled is assumed to be a Markov process with unknown parameters and the The Kalman filter is an efficient Recursive filter that estimates the state of a Dynamic system from a series of noisy measurements Decision theory in Mathematics and Statistics is concerned with identifying the Values uncertainties and other issues relevant in a given In Economics, utility is a measure of the relative satisfaction from or desirability of Consumption of various Goods and services. Starting in the late 80s and early 90s, Judea Pearl and others championed the use of methods drawn from probability theory and economics to devise a number of powerful tools to solve these problems. Judea Pearl is a Computer scientist and Philosopher, best known for developing the probabilistic approach to Artificial intelligence, in Probability is the likelihood or chance that something is the case or will happen Economics is the social science that studies the production distribution, and consumption of goods and services. ^[120]

Bayesian networks^[121] are very general tool that can be used for a large number of problems: reasoning (using the Bayesian inference algorithm),^[122] learning (using the expectation-maximization algorithm),^[123] planning (using decision networks)^[124] and perception (using dynamic Bayesian networks). A Bayesian network (or a belief network) is a Probabilistic graphical model that represents a set of Variables and their probabilistic independencies Bayesian inference is Statistical inference in which evidence or observations are used to update or to newly infer the Probability that a hypothesis may be true Machine learning is a subfield of Artificial intelligence that is concerned with the design and development of Algorithms and techniques that allow computers to "learn" An expectation-maximization ( EM) algorithm is used in Statistics for finding Maximum likelihood estimates of Parameters in probabilistic Automated planning and scheduling is a branch of Artificial intelligence that concerns the realisation of strategies or action sequences typically for execution by An influence diagram (ID (also called a decision network) is a compact graphical and mathematical representation of a decision situation In Computing, machine perception is the ability of computing machines to sense and interpret images sounds or other contents of their environments or of the contents of stored A dynamic Bayesian network is a Bayesian network that represents sequences of variables ^[125]

Probabilistic algorithms can also be used for filtering, prediction, smoothing and finding explanations for streams of data, helping perception systems to analyze processes that occur over time^[126] (e. In Computing, machine perception is the ability of computing machines to sense and interpret images sounds or other contents of their environments or of the contents of stored g. , hidden Markov models^[127] and Kalman filters^[128]). A hidden Markov model ( HMM) is a Statistical model in which the system being modeled is assumed to be a Markov process with unknown parameters and the The Kalman filter is an efficient Recursive filter that estimates the state of a Dynamic system from a series of noisy measurements

Planning problems have also taken advantages of other tools from economics, such as decision theory and decision analysis,^[129] information value theory,^[68] Markov decision processes,^[130] dynamic decision networks,^[130] game theory and mechanism design^[131]

Classifiers and statistical learning methods

Main articles: classifier (mathematics), statistical classification, and machine learning

The simplest AI applications can be divided into two types: classifiers ("if shiny then diamond") and controllers ("if shiny then pick up"). Decision theory in Mathematics and Statistics is concerned with identifying the Values uncertainties and other issues relevant in a given Decision Analysis (DA is the Discipline comprising the Philosophy, Theory, Methodology, and Professional practice necessary to address Markov decision processes (MDPs, named after Andrey Markov, provide a mathematical framework for modeling decision-making in situations where outcomes are partly random and An influence diagram (ID (also called a decision network) is a compact graphical and mathematical representation of a decision situation Game theory is a branch of Applied mathematics that is used in the Social sciences (most notably Economics) Biology, Engineering, In Economics and Game theory, mechanism design is the study of designing rules of a game or system to achieve a specific outcome even though each In Mathematics, a classifier is a mapping from a (discrete or continuous Feature space X to a discrete set of labels Y. Statistical classification is a procedure in which individual items are placed into groups based on quantitative information on one or more characteristics inherent in the items (referred Machine learning is a subfield of Artificial intelligence that is concerned with the design and development of Algorithms and techniques that allow computers to "learn" Controllers do however also classify conditions before inferring actions, and therefore classification forms a central part of many AI systems.

Classifiers^[132] are functions that use pattern matching to determine a closest match. In Mathematics, a classifier is a mapping from a (discrete or continuous Feature space X to a discrete set of labels Y. In Computer science, pattern matching is the act of checking for the presence of the constituents of a given Pattern. They can be tuned according to examples, making them very attractive for use in AI. These examples are known as observations or patterns. In supervised learning, each pattern belongs to a certain predefined class. A class can be seen as a decision that has to be made. All the observations combined with their class labels are known as a data set.

When a new observation is received, that observation is classified based on previous experience. A classifier can be trained in various ways; there are many statistical and machine learning approaches. Machine learning is a subfield of Artificial intelligence that is concerned with the design and development of Algorithms and techniques that allow computers to "learn"

A wide range of classifiers are available, each with its strengths and weaknesses. Classifier performance depends greatly on the characteristics of the data to be classified. There is no single classifier that works best on all given problems; this is also referred to as the "no free lunch" theorem. Various empirical tests have been performed to compare classifier performance and to find the characteristics of data that determine classifier performance. Determining a suitable classifier for a given problem is however still more an art than science.

The most widely used classifiers are the neural network,^[133] kernel methods such as the support vector machine,^[134] k-nearest neighbor algorithm,^[135] Gaussian mixture model,^[136] naive Bayes classifier,^[137] and decision tree. An artificial neural network (ANN, often just called a "neural network" (NN is a Mathematical model or Computational model based on Biological neural Kernel Methods (KMs are a class of algorithms for Pattern analysis, whose best known elementis the Support Vector Machine (SVM Support vector machines ( SVMs) are a set of related Supervised learning methods used for classification and regression. In Pattern recognition, the k -nearest neighbor algorithm ( k -NN is a method for classifying objects based on closest training examples in the In Mathematics, the term mixture model is a model in which independent variables are fractions of a total A naive Bayes classifier is a simple probabilistic classifier based on applying Bayes' theorem with strong (naive independence assumptions In Operations research, specifically in Decision analysis, a decision tree (or tree diagram is a decision support tool that uses a graph or ^[108] The performance of these classifiers have been compared over a wide range of classification tasks^[138] in order to find data characteristics that determine classifier performance.

Neural networks

Main articles: neural networks and connectionism

A neural network is an interconnected group of nodes, akin to the vast network of neurons in the human brain. Traditionally the term neural network had been used to refer to a network or circuit of biological neurons. Connectionism is an approach in the fields of Artificial intelligence, Cognitive psychology / Cognitive science, Neuroscience and Philosophy Neurons (ˈnjuːɹɒn also known as neurones and nerve cells) are responsive cells in the Nervous system that process and transmit information The human brain controls the Central nervous system (CNS by way of the Cranial nerves and Spinal cord, the Peripheral nervous system (PNS

The study of artificial neural networks^[133] began with cybernetics researchers, working in the decade before the field AI research was founded. An artificial neural network (ANN, often just called a "neural network" (NN is a Mathematical model or Computational model based on Biological neural Cybernetics is the interdisciplinary study of the Structure of Complex systems especially Communication processes control mechanisms and Feedback In the 1960s Frank Rosenblatt developed an important early version, the perceptron. Frank Rosenblatt ( 11 July, 1928 &ndash 1971 was a New York City born computer scientist who completed the Perceptron, or MARK 1 computer at The perceptron is a type of Artificial neural network invented in 1957 at the Cornell Aeronautical Laboratory by Frank Rosenblatt. ^[139]

Paul Werbos developed the backpropagation algorithm for multilayer perceptrons in 1974,^[140] which led to a renaissance in neural network research and connectionism in general in the middle 1980s. Paul Werbos is a scientist best known for his 1974 Harvard University Ph Backpropagation, or propagation of error, is a common method of teaching Artificial neural networks how to perform a given task A multilayer perceptron is a Feedforward Artificial neural network model that maps sets of input data onto a set of appropriate output Connectionism is an approach in the fields of Artificial intelligence, Cognitive psychology / Cognitive science, Neuroscience and Philosophy Other common network architectures which have been developed include the feedforward neural network, the radial basis network, the Kohonen self-organizing map and various recurrent neural networks. A feedforward neural network is an Artificial neural network where connections between the units do not form a Directed cycle. A radial basis function network is an Artificial neural network that uses Radial basis functions as activation functions A self-organizing map (SOM is a type of Artificial neural network that is trained using Unsupervised learning to produce a low-dimensional (typically two dimensional A recurrent neural network (RNN is a class of Neural network where connections between units form a Directed cycle. The Hopfield net, a form of attractor network, was first described by John Hopfield in 1982. A Hopfield net is a form of recurrent artificial neural network invented by John Hopfield. John Joseph Hopfield (b July 15, 1933) is an American scientist most widely known for his invention of an associative Neural network

Neural networks are applied to the problem of learning, using such techniques as Hebbian learning^[141] and the relatively new field of Hierarchical Temporal Memory which simulates the architecture of the neocortex. Machine learning is a subfield of Artificial intelligence that is concerned with the design and development of Algorithms and techniques that allow computers to "learn" Hebbian theory describes a basic mechanism for Synaptic plasticity wherein an increase in synaptic efficacy arises from the Presynaptic cell's repeated Hierarchical Temporal Memory (HTM is a Machine learning model developed by Jeff Hawkins and Dileep George of Numenta Inc The neocortex ( Latin for "new Bark " or "new Rind " is a part of the Brain of Mammals It is the outer layer of ^[142]

Social and emergent models

Main article: evolutionary computation

Several algorithms for learning use tools from evolutionary computation, such as genetic algorithms,^[143][144] swarm intelligence. In Computer science evolutionary computation is a subfield of Artificial intelligence (more particularly Computational intelligence) that involves Machine learning is a subfield of Artificial intelligence that is concerned with the design and development of Algorithms and techniques that allow computers to "learn" In Computer science evolutionary computation is a subfield of Artificial intelligence (more particularly Computational intelligence) that involves A genetic algorithm (GA is a Search technique used in Computing to find exact or Approximate solutions to optimization and Search Swarm intelligence (SI is Artificial intelligence based on the Collective behavior of decentralized, self-organized systems ^[145] and genetic programming. In Artificial intelligence, genetic programming (GP is an Evolutionary algorithm based methodology inspired by Biological evolution to find ^[146][147]

Control theory

Main article: intelligent control

Control theory, the grandchild of cybernetics, has many important applications, especially in robotics. Intelligent control is a class of Control techniques that use various AI computing approaches like Neural networks, Bayesian probability, Fuzzy logic Control theory is an interdisciplinary branch of Engineering and Mathematics, that deals with the behavior of Dynamical systems The desired output Cybernetics is the interdisciplinary study of the Structure of Complex systems especially Communication processes control mechanisms and Feedback See also Robot Robotics is the science and technology of Robots and their design manufacture and application ^[148]

Specialized languages

AI researchers have developed several specialized languages for AI research:

• IPL, one of the first programming languages, developed by Alan Newell, Herbert Simon and J. C. Shaw. Information Processing Language (IPL is a Programming language developed by Allen Newell, Cliff Shaw, and Herbert Simon at RAND Corporation Allen Newell ( March 19, 1927 - July 19, 1992) was a researcher in Computer science and Cognitive psychology at the Herbert Alexander Simon ( June 15, 1916 February 9, 2001) was an American Political scientist whose research ranged JC (Cliff Shaw was a systems programmer at the RAND Corporation. ^[149]

• Lisp^[150] was developed by John McCarthy at MIT in 1958. Lisp (or LISP) is a family of Computer Programming languages with a long history and a distinctive fully parenthesized syntax John McCarthy (born September 4, 1927, in Boston, Massachusetts) is an American Computer scientist and Cognitive ^[151] There are many dialects of Lisp in use today.

• Prolog,^[152] a language based on logic programming, was invented by French researchers Alain Colmerauer and Phillipe Roussel, in collaboration with Robert Kowalski of the University of Edinburgh. Prolog is a Logic programming language It is a general purpose language often associated with Artificial intelligence and Computational linguistics Logic programming is in its broadest sense the use of mathematical logic for computer programming This article is about the country For a topic outline on this subject see List of basic France topics. Alain Colmerauer (born 24 January 1941) is a French Computer scientist. Robert "Bob" Anthony Kowalski (born May 15, 1941, in Bridgeport, Connecticut, U The University of Edinburgh (Oilthigh Dhùn Èideann founded in 1582 is a renowned centre for teaching and research in Edinburgh, Scotland, UK. ^[114]

• STRIPS, a planning language developed at Stanford in the 1960s. In Artificial intelligence, STRIPS ( St anford R esearch I nstitute P roblem S olver is an automated planner Leland Stanford Junior University, commonly known as Stanford University or simply Stanford, is a private Research university located in
• Planner developed at MIT around the same time. Planner (often seen in publications as "PLANNER" although it is not an acronym is a Programming language designed by Carl Hewitt at MIT, and

AI applications are also often written in standard languages like C++ and languages designed for mathematics, such as Matlab and Lush. C++ (" C Plus Plus " ˌsiːˌplʌsˈplʌs is a general-purpose Programming language. MATLAB is a numerical computing environment and Programming language. Lush, (Lisp Universal Shell is an object-oriented dialect of the Lisp programming language that was initially developed as a Scripting language for

Evaluating artificial intelligence

Main article: Progress in artificial intelligence

How can one determine if an agent is intelligent? In 1950, Alan Turing proposed a general procedure to test the intelligence of an agent now known as the Turing test. Artificial intelligence can be evaluated on constrained and well-defined problems that allow comparison with human performance The Turing test is a proposal for a test of a Machine 's ability to demonstrate intelligence This procedure allows almost all the major problems of artificial intelligence to be tested. However, it is a very difficult challenge and at present all agents fail.

Artificial intelligence can also be evaluated on specific problems such as small problems in chemistry, hand-writing recognition and game-playing. Such tests have been termed subject matter expert Turing tests. A subject matter expert Turing test is a variation of the Turing test where a computer system attempts to replicate an expert in a given field such as Chemistry or Smaller problems provide more achievable goals and there are an ever-increasing number of positive results.

The broad classes of outcome for an AI test are:

• optimal: it is not possible to perform better
• strong super-human: performs better than all humans
• super-human: performs better than most humans
• sub-human: performs worse than most humans

For example, performance at checkers is optimal,^[153] performance at chess is super-human and nearing strong super-human,^[154] and performance at many everyday tasks performed by humans is sub-human.

Competitions and prizes

Main article: Competitions and prizes in artificial intelligence

There are a number of competitions and prizes to promote research in artificial intelligence. There are a number of competitions and prizes to promote research in Artificial intelligence. The main areas promoted are: general machine intelligence, conversational behaviour, data-mining, driverless cars, robot soccer and games.

Applications of artificial intelligence

Main article: Applications of artificial intelligence

Artificial intelligence has successfully been used in a wide range of fields including medical diagnosis, stock trading, robot control, law, scientific discovery and toys. Artificial intelligence has been used in a wide range of fields including Medical diagnosis, Stock trading, Robot control, Law, scientific Diagnosis is the identification by Process of elimination, of the nature of anything A stock trader or a stock investor is an Individual or firm who buys and sells Stocks or bonds (and possibly other Robot control is the study of controlling robots. See also Control theory Mobile robot navigation Law is a system of rules enforced through a set of Institutions used as an instrument to underpin civil obedience politics economics and society Frequently, when a technique reaches mainstream use it is no longer considered artificial intelligence, sometimes described as the AI effect. ^[155] It may also become integrated into artificial life. Artificial life (commonly Alife or alife) is a field of study and an associated art form which examine Systems related to Life, its processes

See also

• List of basic artificial intelligence topics
• List of AI researchers
• List of AI projects
• List of important AI publications
• List of emerging technologies

Notes

References

Major AI textbooks

• Luger, George & Stubblefield, William (2004), Artificial Intelligence: Structures and Strategies for Complex Problem Solving (5th ed. ), The Benjamin/Cummings Publishing Company, Inc. , pp. 720, ISBN 0-8053-4780-1, <http://www.cs.unm.edu/~luger/ai-final/tocfull.html> 
• Nilsson, Nils (1998), Artificial Intelligence: A New Synthesis, Morgan Kaufmann Publishers, ISBN 978-1-55860-467-4 
• Russell, Stuart J. & Norvig, Peter (2003), Artificial Intelligence: A Modern Approach (2nd ed. Nils J Nilsson is one of the founding researchers in the discipline of Artificial intelligence. Stuart Russell (born 1962) is a computer scientist known for his contributions to Artificial intelligence. Peter Norvig is an American computer scientist. He is currently the Director of Research (formerly Director of Search Quality at Google Inc Artificial Intelligence A Modern Approach (ISBN 0-13-790395-2 (AIMA is a college textbook on Artificial Intelligence, written by Stuart J ), Upper Saddle River, NJ: Prentice Hall, ISBN 0-13-790395-2, <http://aima.cs.berkeley.edu/> 
• Poole, David; Mackworth, Alan & Goebel, Randy (1998), Computational Intelligence: A Logical Approach, Oxford University Press, <http://www.cs.ubc.ca/spider/poole/ci.html> 

Other sources

• ACM, (Association of Computing Machinery) (1998), ACM Computing Classification System: Artificial intelligence, <http://www.acm.org/class/1998/I.2.html> 
• Brooks, Rodney (1990), “Elephants Don't Play Chess”, Robotics and Autonomous Systems 6: 3-15, <http://people.csail.mit.edu/brooks/papers/elephants.pdf>. The Association for Computing Machinery, or ACM, was founded in 1947 as the world's first scientific and educational Computing society Rodney Allen Brooks (b December 30, 1954, in Adelaide, Australia) is Panasonic Professor of Robotics at the Massachusetts Institute Retrieved on 30 August 2007 
• Buchanan, Bruce G. (2005), “A (Very) Brief History of Artificial Intelligence”, AI Magazine: 53-60, <http://www.aaai.org/AITopics/assets/PDF/AIMag26-04-016.pdf>. Retrieved on 30 August 2007 
• Crevier, Daniel (1993), AI: The Tumultuous Search for Artificial Intelligence, New York, NY: BasicBooks, ISBN 0-465-02997-3 
• Haugeland, John (1985), Artificial Intelligence: The Very Idea, Cambridge, Mass. Daniel Crevier (born 1947 is a Canadian Entrepreneur and Artificial intelligence and Image processing researcher John Haugeland (born in 1945 is a professor of Philosophy at the University of Chicago, where he chairs the : MIT Press, ISBN 0-262-08153-9 .
• Hawkins, Jeff & Blakeslee, Sandra (2004), On Intelligence, New York, NY: Owl Books, ISBN 0-8050-7853-3 . Jeff Hawkins (born June 1, 1957 in Huntington New York) is the founder of Palm Computing (where he invented the Palm Pilot)
• Kahneman, Daniel; Slovic, D. Daniel Kahneman (דניאל כהנמן (born 5 March 1934 is an Israeli American psychologist and Nobel laureate, notable for his work on & Tversky, Amos (1982), Judgment under uncertainty: Heuristics and biases, New York: Cambridge University Press . Amos Nathan Tversky, PhD (עמוס טברסקי March 16, 1937 - June 2, 1996) was a cognitive and mathematical psychologist
• Kurzweil, Ray (1999), The Age of Spiritual Machines, Penguin Books, ISBN 0-670-88217-8 
• Kurzweil, Ray (2005), The Singularity is Near, Penguin Books, ISBN 0-670-03384-7 
• Lakoff, George & Núñez, Rafael E. (2000), Where Mathematics Comes From: How the Embodied Mind Brings Mathematics into Being, Basic Books, ISBN 0-465-03771-2 . Raymond Kurzweil (kɚzwaɪl (born February 12 1948 is an inventor and Futurist. Raymond Kurzweil (kɚzwaɪl (born February 12 1948 is an inventor and Futurist. "Lakoff" and "Professor Lakoff" redirect here Rafael Núñez may refer to Rafael Núñez (politician, President of Colombia in the 1880s and 1890s Rafael E Where Mathematics Comes From How the Embodied Mind Brings Mathematics into Being (hereinafter WMCF) is a book by George Lakoff, a cognitive linguist
• Lenat, Douglas (1989), Building Large Knowledge-Based Systems, Addison-Wesley 
• Lighthill, Professor Sir James (1973), “Artificial Intelligence: A General Survey”, Artificial Intelligence: a paper symposium, Science Research Council 
• McCarthy, John; Minsky, Marvin; Rochester, Nathan & Shannon, Claude (1955), A Proposal for the Dartmouth Summer Research Project on Artificial Intelligence, <http://www-formal.stanford.edu/jmc/history/dartmouth/dartmouth.html> . Douglas B Lenat (born in 1950 is the CEO of Cycorp Inc of Austin Texas, and has been a prominent researcher in Artificial intelligence, Sir Michael James Lighthill, FRS ( 23 January 1924 – 17 July 1998) was a British applied mathematician John McCarthy (born September 4, 1927, in Boston, Massachusetts) is an American Computer scientist and Cognitive Marvin Lee Minsky (born August 9, 1927) is an American cognitive scientist in the field of Artificial intelligence (AI co-founder Nathaniel Rochester Nathan Rochester ( January 14, 1919 &ndash June 8, 2001) designed the IBM 701, wrote the first assembler Claude Elwood Shannon (April 30 1916 – February 24 2001 an American Electronic engineer and Mathematician, is "the father of Information
• McCarthy, John & Hayes, P. John McCarthy (born September 4, 1927, in Boston, Massachusetts) is an American Computer scientist and Cognitive J. (1969), “Some philosophical problems from the standpoint of artificial intelligence”, Machine Intelligence 4: 463-502, <http://www-formal.stanford.edu/jmc/mcchay69.html> 
• McCorduck, Pamela (2004), Machines Who Think (2nd ed. ), Natick, MA: A. K. Peters, Ltd. , ISBN 1-56881-205-1 .
• Minsky, Marvin (1967), Computation: Finite and Infinite Machines, Englewood Cliffs, N. Marvin Lee Minsky (born August 9, 1927) is an American cognitive scientist in the field of Artificial intelligence (AI co-founder J. : Prentice-Hall 
• Minsky, Marvin (2006), The Emotion Machine, New York, NY: Simon & Schusterl, ISBN 0-7432-7663-9 
• Moravec, Hans (1976), The Role of Raw Power in Intelligence, <http://www.frc.ri.cmu.edu/users/hpm/project.archive/general.articles/1975/Raw.Power.html> 
• Moravec, Hans (1988), Mind Children, Harvard University Press 
• NRC (1999), “Developments in Artificial Intelligence”, Funding a Revolution: Government Support for Computing Research, National Academy Press 
• Newell, Allen & Simon, H. A. (1963), “GPS: A Program that Simulates Human Thought”, in Feigenbaum, E. Marvin Lee Minsky (born August 9, 1927) is an American cognitive scientist in the field of Artificial intelligence (AI co-founder Hans Moravec (born November 30 1948 in Austria) is a research Professor at the Robotics Institute (Carnegie Mellon of Carnegie Hans Moravec (born November 30 1948 in Austria) is a research Professor at the Robotics Institute (Carnegie Mellon of Carnegie The National Research Council (NRC of the USA is the working arm of the United States National Academy of Sciences and the United States National Academy of Allen Newell ( March 19, 1927 - July 19, 1992) was a researcher in Computer science and Cognitive psychology at the Herbert Alexander Simon ( June 15, 1916 February 9, 2001) was an American Political scientist whose research ranged A. & Feldman, J. , Computers and Thought, McGraw-Hill 
• Searle, John (1980), “Minds, Brains and Programs”, Behavioral and Brain Sciences 3 (3): 417-457, <http://www.bbsonline.org/documents/a/00/00/04/84/bbs00000484-00/bbs.searle2.html> 
• Shapiro, Stuart C. John Rogers Searle (born July 31 1932 in Denver Colorado) is an American Philosopher and the Slusser Professor of Philosophy at the University (1992), “Artificial Intelligence”, in Shapiro, Stuart C. , Encyclopedia of Artificial Intelligence (2nd ed. ), New York: John Wiley, pp. 54-57, <http://www.cse.buffalo.edu/~shapiro/Papers/ai.ps> .
• Simon, H. A. (1965), The Shape of Automation for Men and Management, New York: Harper & Row 
• Turing, Alan (October 1950), “Computing machinery and intelligence”, Mind LIX (236): 433-460, ISSN 0026-4423, doi:10.1093/mind/LIX.236.433, <http://loebner.net/Prizef/TuringArticle.html> 
• Wason, P. C. (1966), “Reasoning”, in Foss, B. Herbert Alexander Simon ( June 15, 1916 February 9, 2001) was an American Political scientist whose research ranged Alan Mathison Turing, OBE, FRS (ˈt(jʊ(ərɪŋ (23 June 1912 &ndash 7 June 1954 was an English Mathematician Computing Machinery and Intelligence, written by Alan Turing and published in 1950 in Mind, is a seminal paper on the topic of Artificial An International Standard Serial Number ( ISSN) is a unique eight-digit number used to identify a print or electronic Periodical publication. A digital object identifier ( DOI) is a permanent identifier given to an Electronic document. Peter Cathcart Wason (22 April 1924 - 17 April 2003 was a cognitive psychologist, who worked on the Psychology of reason. M. , New horizons in psychology, Harmondsworth: Penguin 
• Weizenbaum, Joseph (1976), Computer Power and Human Reason, San Francisco: W. Joseph Weizenbaum ( Berlin, January 8, 1923 – March 5, 2008) was a German-American author and professor emeritus of H. Freeman & Company, ISBN 0716704641 

Further reading

• R. Sun & L. Bookman, (eds. ), Computational Architectures: Integrating Neural and Symbolic Processes. Kluwer Academic Publishers, Needham, MA. 1994.

External links

• AI at the Open Directory Project
• AI-Tools, the Open Source AI community homepage
• Artificial Intelligence Directory, a directory of Web resources related to artificial intelligence
• AI community with news, links, downloads, and articles
• The Association for the Advancement of Artificial Intelligence
• Freeview Video 'Machines with Minds' by the Vega Science Trust and the BBC/OU
• John McCarthy's frequently asked questions about AI
• The Futurist magazine interviews "Ai chasers" Rodney Brooks, Peter Norvig, Barney Pell, et al.
• Jonathan Edwards looks at AI (BBC audio)С
• Ray Kurzweil's website dedicated to AI including prediction of future development in AI
• International Journal of Computational Intelligence
• International Journal of Intelligent Technology
• Logic and Artificial Intelligence entry at the Stanford Encyclopedia of Philosophy by Richmond Thomason