Garry Kasparov playing against Deep Blue, the first machine to win a chess match against a reigning world champion.

Artificial intelligence Portal

The modern definition of artificial intelligence (or AI) is "the study and design of intelligent agents" where an intelligent agent is a system that perceives its environment and takes actions which maximizes its chances of success.^[1] John McCarthy, who coined the term in 1956,^[2] defines it as "the science and engineering of making intelligent machines."^[3] Other names for the field have been proposed, such as computational intelligence,^[4] synthetic intelligence^[5] or computational rationality.^[6] This is a disambiguation page — a navigational aid which lists other pages that might otherwise share the same title. ... Image File history File links Garry Kasparov playing Deep Blue in 1997. ... Image File history File links Garry Kasparov playing Deep Blue in 1997. ... Garry Kimovich Kasparov (IPA: ; Russian: ) (born April 13, 1963, in Baku, Azerbaijan SSR; now Azerbaijan) is a Russian chess grandmaster, former World Chess Champion, writer and political activist. ... Kasparov vs. ... Image File history File links Portal. ... It has been suggested that this article or section be merged with software agent. ... John McCarthy (born September 4, 1927, in Boston, Massachusetts, sometimes known affectionately as Uncle John McCarthy), is a prominent computer scientist who received the Turing Award in 1971 for his major contributions to the field of Artificial Intelligence. ... Computational intelligence (CI) is a branch of artificial intelligence. ... It has been suggested that this article or section be merged into Artificial Intelligence. ...

The term artificial intelligence is also used to describe a property of machines or programs: the intelligence that the system demonstrates. Among the traits that researchers hope machines will exhibit are reasoning, knowledge, planning, learning, communication, perception and the ability to move and manipulate objects.^[7] General intelligence (or "strong AI") has not yet been achieved and is a long-term goal of AI research.^[8] Intelligence is the mental capacity to reason, plan, solve problems, think abstractly, comprehend ideas and language, and learn. ... For the strong AI hypothesis, see philosophy of artificial intelligence Strong AI is a term used by futurists, science fiction writers and forward looking researchers to describe artificial intelligence that matches or exceeds human intelligence. ...

AI research uses tools and insights from many fields, including computer science, psychology, philosophy, neuroscience, cognitive science, linguistics, operations research, economics, control theory, probability, optimization and logic.^[9] AI research also overlaps with tasks such as robotics, control systems, scheduling, data mining, logistics, speech recognition, facial recognition and many others.^[10] Computer science, or computing science, is the study of the theoretical foundations of information and computation and their implementation and application in computer systems. ... Psychological science redirects here. ... For other uses, see Philosophy (disambiguation). ... Drawing of the cells in the chicken cerebellum by S. Ramón y Cajal Neuroscience is a field that is devoted to the scientific study of the nervous system. ... Cognitive science is usually defined as the scientific study either of mind or of intelligence (e. ... Computational linguistics is an interdisciplinary field dealing with the statistical and logical modeling of natural language from a computational perspective. ... Operations Research or Operational Research (OR) is an interdisciplinary branch of mathematics which uses methods like mathematical modeling, statistics, and algorithms to arrive at optimal or good decisions in complex problems which are concerned with optimizing the maxima (profit, faster assembly line, greater crop yield, higher bandwidth, etc) or minima... Computational economics is a form of economics which relies on mathematical methods, including mathematical economics and econometrics. ... For control theory in psychology and sociology, see control theory (sociology). ... Probability is the likelihood 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 by systematically choosing the values of real or integer variables from within an allowed set. ... Logic (from Classical Greek λόγος logos; meaning word, thought, idea, argument, account, reason, or principle) is the study of the principles and criteria of valid inference and demonstration. ... The Shadow robot hand system holding a lightbulb. ... A control system is a device or set of devices to manage, command, direct or regulate the behaviour 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 intelligent agents, autonomous robots and unmanned vehicles. ... Data mining is the principle of sorting through large amounts of data and picking out relevant information. ... Look up Logistics in Wiktionary, the free dictionary. ... Speech recognition (in many contexts also known as automatic speech recognition, computer speech recognition or erroneously as voice recognition) is the process of converting a speech signal to a sequence of words in the form of digital data, by means of an algorithm implemented as a computer program. ... A facial recognition system is a computer-driven application for automatically identifying a person from a digital image. ...

Perspectives on AI

The rise and fall of AI in public perception

Main articles: History of artificial intelligence and Timeline of artificial intelligence

See also: AI Winter

The notion of artificial intelligence dates back to classical antiquity, however it was not until the advent of the modern programmable digital computer that scientists began to seriously consider information processing as the key to building intelligent machines. The field was born at a conference on the campus of Dartmouth College in the summer of 1956.^[11] 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. They and their students wrote programs that were, to most people, simply astonishing:^[12] computers were solving word problems in algebra, proving logical theorems and speaking English.^[13] By the middle 60s their research was heavily funded by DARPA,^[14] and they were optimistic about the future of the new field: Artificial Intelligence was founded in the early 1950s by an eclectic group of visionaries who claimed to be on the verge of changing the world and mans place in it. ... See also: History of artificial intelligence // ^ Russell & Norvig 2003, p. ... To meet Wikipedias quality standards, this article may require cleanup. ... Classical antiquity is a broad term for a long period of cultural history centered on the Mediterranean Sea, which begins roughly with the earliest-recorded Greek poetry of Homer (7th century BC), and continues through the rise of Christianity and the fall of the Western Roman Empire (5th century AD... This article is about the machine. ... The ASCII codes for the word Wikipedia represented in binary, the numeral system most commonly used for encoding computer information. ... Dartmouth College is a private, coeducational university located in Hanover, New Hampshire, USA. Incorporated as Trustees of Dartmouth College,[6][7] it is a member of the Ivy League and one of the nine colonial colleges founded before the American Revolution. ... John McCarthy (born September 4, 1927, in Boston, Massachusetts, sometimes known affectionately as Uncle John McCarthy), is a prominent computer scientist who received the Turing Award in 1971 for his major contributions to the field of Artificial Intelligence. ... Marvin Lee Minsky (born August 9, 1927), sometimes affectionately known as Old Man Minsky, is an American cognitive scientist in the field of artificial intelligence (AI), co-founder of MITs AI laboratory, and author of several texts on AI and philosophy. ... Allen Newell (March 19, 1927 - July 19, 1992) was a researcher in computer science and cognitive psychology at the RAND corporation and at Carnegie-Mellon’s School of Computer Science. ... Herbert Alexander Simon (June 15, 1916 – February 9, 2001) was an American political scientist whose research ranged across the fields of cognitive psychology, computer science, public administration, economics, management, and philosophy of science and a professor, most notably, at Carnegie Mellon University. ... Mapúa Institute of Technology (MIT, MapúaTech or simply Mapúa) is a private, non-sectarian, Filipino tertiary institute located in Intramuros, Manila. ... CMU is an acronym for three different universities: Carnegie Mellon University in Pittsburgh, Pennsylvania Central Michigan University in Mount Pleasant, Michigan Chiang Mai University in Chiangmai, Thailand Central Michigan University claims CMU as a trademark: [1]. A search through the United States Patent and Trademark Offices trademark database will... Stanford may refer: Stanford University Places: Stanford, Kentucky Stanford, California, home of Stanford University Stanford Shopping Center Stanford, New York, town in Dutchess County. ... The Defense Advanced Research Projects Agency (DARPA) is an agency of the United States Department of Defense responsible for the development of new technology for use by the military. ...

• 1965, H. A. Simon: "machines will be capable, within twenty years, of doing any work a man can do"^[15]
• 1967, Marvin Minsky: "Within a generation ... the problem of creating 'artificial intelligence' will substantially be solved."^[16]

These predictions, and many like them, would not come true. They had failed to recognize the difficulty of some of the problems they faced. In 1974, in response to the criticism of England's Sir James Lighthill and ongoing pressure from congress to fund more productive projects, DARPA cut off all undirected, exploratory research in AI. This was the first AI Winter.^[17] Herbert Alexander Simon (June 15, 1916 – February 9, 2001) was an American political scientist whose research ranged across the fields of cognitive psychology, computer science, public administration, economics, management, and philosophy of science and a professor, most notably, at Carnegie Mellon University. ... Marvin Lee Minsky (born August 9, 1927), sometimes affectionately known as Old Man Minsky, is an American cognitive scientist in the field of artificial intelligence (AI), co-founder of MITs AI laboratory, and author of several texts on AI and philosophy. ... Sir Michael James Lighthill FRS (23 January 1924 - 17 July 1998) was a British applied mathematician, known for his pioneering work in the field of Aeroacoustics. ... The Defense Advanced Research Projects Agency (DARPA) is an agency of the United States Department of Defense responsible for the development of new technology for use by the military. ... To meet Wikipedias quality standards, this article may require cleanup. ...

In the early 80s, the field was revived by the commercial success of expert systems and by 1985 the market for AI had reached more than a billion dollars.^[18] Minsky and others warned the community that enthusiasm for AI had spiraled out of control and that disappointment was sure to follow.^[19] Minsky was right. 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.^[20] An expert system is a class of computer programs developed by researchers in artificial intelligence during the 1970s and applied commercially throughout the 1980s. ... Marvin Lee Minsky (born August 9, 1927), sometimes affectionately known as Old Man Minsky, is an American cognitive scientist in the field of artificial intelligence (AI), co-founder of MITs AI laboratory, and author of several texts on AI and philosophy. ... Marvin Lee Minsky (born August 9, 1927), sometimes affectionately known as Old Man Minsky, is an American cognitive scientist in the field of artificial intelligence (AI), co-founder of MITs AI laboratory, and author of several texts on AI and philosophy. ... The original Lisp machine built by Greenblatt and Knight Lisp machines were general-purpose computers designed (usually through hardware support) to efficiently run Lisp as their main software language. ... To meet Wikipedias quality standards, this article may require cleanup. ...

In the 90s 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.^[21] 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.^[22] Look up Logistics in Wiktionary, the free dictionary. ... Data mining is the principle of sorting through large amounts of data and picking out relevant information. ... Diagnosis (from the Greek words dia = by and gnosis = knowledge) is the process of identifying a disease by its signs, symptoms and results of various diagnostic procedures. ... Gordon Moores original graph from 1965 Growth of transistor counts for Intel processors (dots) and Moores Law (upper line=18 months; lower line=24 months) For the observation regarding information retrieval, see Mooers Law. ...

The philosophy of AI

Mind and Brain Portal

Main articles: Philosophy of artificial intelligence and Ethics of artificial intelligence

The strong AI vs. weak AI debate ("can a man-made artifact be conscious?") is still a hot topic amongst AI philosophers. This involves philosophy of mind and the mind-body problem. Most notably Roger Penrose in his book The Emperor's New Mind and John Searle with his "Chinese room" thought experiment argue that true consciousness cannot be achieved by formal logic systems, while Douglas Hofstadter in Gödel, Escher, Bach and Daniel Dennett in Consciousness Explained argue in favour of functionalism. In many strong AI supporters' opinions, artificial consciousness is considered the holy grail of artificial intelligence. Edsger Dijkstra famously opined that the debate had little importance: "The question of whether a computer can think is no more interesting than the question of whether a submarine can swim." Image File history File links Portal. ... The philosophy of artificial intelligence concerns questions of artificial intelligence (AI) such as: What is intelligence? How can one recognize its presence and applications? Is it possible for machines to exhibit intelligence? Does the presence of human-like intelligence imply consciousness and emotions? Is creating human-like artificial intelligence moral... There are many ethical problems associated with working to create intelligent creatures. ... The philosophy of artificial intelligence concerns questions of artificial intelligence (AI) such as: What is intelligence? How can one recognize its presence and applications? Is it possible for machines to exhibit intelligence? Does the presence of human-like intelligence imply consciousness and emotions? Is creating human-like artificial intelligence moral... A philosopher is a person who thinks deeply regarding people, society, the world, and/or the universe. ... A phrenological mapping of the brain. ... To meet Wikipedias quality standards, this article may require cleanup. ... Sir Roger Penrose, OM, FRS (born 8 August 1931) is an English mathematical physicist and Emeritus Rouse Ball Professor of Mathematics at the Mathematical Institute, University of Oxford and Emeritus Fellow of Wadham College. ... The Emperors New Mind: Concerning Computers, Minds and The Laws of Physics is a 1989 book by mathematical physicist Roger Penrose. ... John Rogers Searle (born July 31, 1932 in Denver, Colorado) is the Slusser Professor of Philosophy at the University of California, Berkeley, and is noted for contributions to the philosophy of language, philosophy of mind and consciousness, on the characteristics of socially constructed versus physical realities, and on practical reason. ... This article or section does not cite its references or sources. ... In philosophy, physics, and other fields, a thought experiment (from the German Gedankenexperiment) is an attempt to solve a problem using the power of human imagination. ... Consciousness is a quality of the mind generally regarded to comprise qualities such as subjectivity, self-awareness, sentience, sapience, and the ability to perceive the relationship between oneself and ones environment. ... Logic (from ancient Greek λόγος (logos), meaning reason) is the study of arguments. ... Douglas Richard Hofstadter (born February 15, 1945 in New York, New York) is an American academic. ... Gödel, Escher, Bach: an Eternal Golden Braid: A metaphorical fugue on minds and machines in the spirit of Lewis Carroll (commonly GEB) is a Pulitzer Prize (1980)-winning book by Douglas Hofstadter, published in 1979 by Basic Books. ... Daniel Clement Dennett (born March 28, 1942 in Boston, Massachusetts) is a prominent American philosopher whose research centers on philosophy of mind, philosophy of science and philosophy of biology, particularly as those fields relate to evolutionary biology and cognitive science. ... Cover of Consciousness Explained Consciousness Explained (published 1991) is a controversial book by the American philosopher Daniel Dennett which attempts to explain how consciousness arises from interaction of physical and cognitive processes in the brain. ... Functionalism is a theory of the mind in contemporary philosophy, developed largely as an alternative to both the identity theory of mind and behaviorism. ... Artificial consciousness (AC), also known as machine consciousness (MC) or synthetic consciousness, is a field related to artificial intelligence and cognitive robotics whose aim is to define that which would have to be synthesized were consciousness to be found in an engineered artifact. ... For other uses, see Holy Grail (disambiguation). ... Edsger Dijkstra Edsger Wybe Dijkstra (Rotterdam, May 11, 1930 – Nuenen, August 6, 2002; IPA: ) was a Dutch computer scientist. ...

Epistemology, the study of knowledge, also makes contact with AI, as engineers find themselves debating similar questions to philosophers about how best to represent and use knowledge and information (e.g., semantic networks). Theory of knowledge redirects here: for other uses, see theory of knowledge (disambiguation) According to Plato, knowledge is a subset of that which is both true and believed Epistemology or theory of knowledge is the branch of philosophy that studies the nature, methods, limitations, and validity of knowledge and belief. ... A semantic network is often used as a form of knowledge representation. ...

AI in myth and fiction

Main article: Artificial intelligence in fiction

Beings created by man have existed in mythology long before their currently imagined embodiment in electronics (and to a lesser extent biochemistry). Some notable examples include: Golems, and Frankenstein. These, and our modern science fiction stories, enables us to imagine that the fundamental problems of perception, knowledge representation, common sense reasoning, and learning have been solved and let's us consider the technology's impact on society. With Artificial Intelligence's theorized potential equal to or greater than our own, the impact can range from service (R2D2), cooperation (Lt. Commander Data), and/or human enhancement (Ghost in the Shell) to our domination (With Folded Hands) or extermination (Terminator (series), The Matrix (series), Battlestar Galactica (re-imagining)). Given the negative consequences, ranging from fear of losing one's job to an AI, the clouding of our self image, to the extreme of the AI Apocalypse, it is not surprising the Frankenstein complex would be a common reaction. Subconsciously we demonstrate this same fear in the Uncanny Valley hypothesis. See AI and Society in fiction for more ... This is a sub-article of Artificial intelligence (AI), describing the different futuristic portrayals of fictional artificial intelligence. ... This article is about a field of research. ... This article is about the engineering discipline. ... Biochemistry (from Greek: , bios, life and Egyptian kēme, earth[1]) is the study of the chemical processes in living organisms. ... For other uses, see Golem (disambiguation). ... This article is about the 1818 novel. ... Science fiction is a form of speculative fiction principally dealing with the impact of imagined science and technology, or both, upon society and persons as individuals. ... In psychology and the cognitive sciences, perception is the process of acquiring, interpreting, selecting, and organizing sensory information. ... Knowledge representation is an issue that arises in both cognitive science and artificial intelligence. ... Commonsense reasoning is the branch of Artificial intelligence concerned with replicating human thinking. ... Learning is the acquisition and development of memories and behaviors, including skills, knowledge, understanding, values, and wisdom. ... R2-D2 (also spelled Artoo-Detoo, called R2 for short), is an astromech droid and colleague of C-3PO in the fictional Star Wars universe. ... Data[1] is a character, portrayed by Brent Spiner, in the Star Trek fictional universe. ... Motoko Kusanagi from the manga Ghost in the Shell. ... With Folded Hands is a 1947 science fiction short story by Jack Williamson (1908-2006). ... This article is about the entire Terminator franchise. ... The Matrix series is a media franchise consisting primarily of three films: The Matrix, The Matrix Reloaded and The Matrix Revolutions. ... The Battlestar Galactica science fiction franchise, which began as a 1978 TV series, was reimagined in 2003 into the TV miniseries. ... In Isaac Asimovs robot novels, the Frankenstein complex is a colloquial term for the fear of robots. ... Repliee Q2 The Uncanny Valley is a hypothesis about robotics concerning the emotional response of humans to robots and other non-human entities. ... This is a sub-article of Artificial intelligence (AI), describing the different futuristic portrayals of fictional artificial intelligence. ...

With the capabilities of a human, a sentient AI can play any of the roles normally ascribed to humans in a narrative, such as protagonist (Bicentennial Man (film)), antagonist (Terminator, HAL 9000), faithful companion (R2D2), cometic relief (C3PO). See Sentient AI in fiction for more ... Sentient computers are found in a number of science fiction stories, films and TV series. ... To meet Wikipedias quality standards, this article or section may require cleanup. ... A protagonist is the main figure of a piece of literature or drama and has the main part or role. ... Bicentennial Man is a 1999 film starring Robin Williams based on the well-known novella of the same name by Isaac Asimov. ... For other uses, see Antagonist (disambiguation). ... An 800-series terminator endoskeleton, a robot-only version of the cyborg played by Arnold Schwarzenegger. ... HAL 9000 (Heuristically programmed ALgorithmic computer) is a fictional character in Arthur C. Clarkes Space Odyssey saga. ... R2-D2 (also spelled Artoo-Detoo, called R2 for short), is an astromech droid and colleague of C-3PO in the fictional Star Wars universe. ... C-3PO (pronounced See-Threepio, called 3PO for short) is a character from the fictional Star Wars universe. ... This is a sub-article of Artificial intelligence (AI), describing the different futuristic portrayals of fictional artificial intelligence. ...

While most portrayals of AI in science fiction deal with sentient AIs, many imagined futures incorporate AI subsystems in their vision: such as self-navigating cars and speech recognition systems. See non-sentient AI in fiction for more ... Science fiction is a form of speculative fiction principally dealing with the impact of imagined science and technology, or both, upon society and persons as individuals. ... Sentience is the capacity for basic consciousness -- the ability to feel or perceive, not necessarily including the faculty of self-awareness. ... Speech recognition (in many contexts also known as automatic speech recognition, computer speech recognition or erroneously as voice recognition) is the process of converting a speech signal to a sequence of words in the form of digital data, by means of an algorithm implemented as a computer program. ... This is a sub-article of Artificial intelligence (AI), describing the different futuristic portrayals of fictional artificial intelligence. ...

The inevitability of the integration of AI into human society is also argued by some science/futurist writers such as Kevin Warwick and Hans Moravec and the manga Ghost in the Shell Kevin Warwick speaking at the Tomorrows People conference in 2006 hosted by Oxford University. ... Hans Moravec (born November 30, 1948 in Austria) is a research professor at the Robotics Institute (Carnegie Mellon) of Carnegie Mellon University. ... Motoko Kusanagi from the manga Ghost in the Shell. ...

The future of AI

Main article: Strong AI

For the strong AI hypothesis, see philosophy of artificial intelligence Strong AI is a term used by futurists, science fiction writers and forward looking researchers to describe artificial intelligence that matches or exceeds human intelligence. ...

AI research

Problems of AI

While there is no universally accepted definition of intelligence,^[23] AI researchers have studied several traits that are considered essential.^[7]

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.^[24] These early methods often couldn't be applied to real world situations because the were unable to handle incomplete or imprecise information. However, by the late 80s and 90s, AI research developed highly successful methods for dealing with uncertainty, employing concepts from probability and economics.^[25] “Uncertain” redirects here. ... Probability is the likelihood that something is the case or will happen. ... Face-to-face trading interactions on the New York Stock Exchange trading floor. ...

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. The search for more efficient problem solving algorithms is a high priority for AI research.^[26] In cryptanalysis, a brute force attack on a cipher is a brute-force search of the key space; that is, testing all possible keys, in an attempt to recover the plaintext used to produce a particular ciphertext. ...

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.^[27] For many problems, people seem to simply jump to the correct solution: they think "instinctively" and "unconsciously". These instincts seem to involve skills usually applied to other problems, such as motion and manipulation (our so-called "embodied" skills that allow us deal with the physical world) or perception (for example, our skills at pattern matching). It is hoped that sub-symbolic methods, like computational intelligence and situated AI, will be able to model these instinctive skills. The problem of unconscious problem solving, which forms part of our commonsense reasoning, is largely unsolved. Cognitive science is usually defined as the scientific study either of mind or of intelligence (e. ... Look up Unconscious in Wiktionary, the free dictionary. ... Embodiment is the way in which human (or any other animals) psychology arises from the brains and bodys physiology. ... In computer science, pattern matching is the act of checking for the presence of the constituents of a given pattern. ... Computational intelligence (CI) is a branch of artificial intelligence. ... In artificial intelligence, the term situated refers to an agent which is embedded in an environment. ... Commonsense reasoning is the branch of Artificial intelligence concerned with replicating human thinking. ...

Knowledge representation

Main articles: knowledge representation and commonsense knowledge

Another important measure of intelligence is how much an agent knows. Many of the problems machines are expected to solve will require extensive knowledge about the world. Knowledge representation^[28] and knowledge engineering^[29] are central to AI research. Among the things that AI needs to represent are: objects, properties, categories and relations between objects;^[30] situations, events, states and time;^[31] causes and effects;^[32] knowledge about knowledge (what we know about what other people know);^[33] and many other, less well researched domains. A complete representation of "what exists" is an ontology^[34] (borrowing a word from traditional philosophy). Ontological engineering is the science of finding a general representation that can handle all of human knowledge. Knowledge representation is an issue that arises in both cognitive science and artificial intelligence. ... Commonsense reasoning is the branch of Artificial intelligence concerned with replicating human thinking. ... Simple reflex agent Learning agent The terms agent and intelligent agent are ambiguous and have been used in two different, but related senses, which are often confused. ... Knowledge representation is an issue that arises in both cognitive science and artificial intelligence. ... The process of building knowledge-based systems is called knowledge engineering (KE). ... In both computer science and information science, an ontology is a data model that represents a set of concepts within a domain and the relationships between those concepts. ... For other uses, see Philosophy (disambiguation). ...

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." For example, if a bird comes up in conversation, people typically picture a 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^[35] as the qualification problem: for any commonsense rule that AI researchers care to represent, there tend to be a huge number of exceptions. 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.^[36]
• 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.
• The breadth of common sense knowledge: The number of atomic facts that the average person knows is astronomical. 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.^[37]

John McCarthy (born September 4, 1927, in Boston, Massachusetts, sometimes known affectionately as Uncle John McCarthy), is a prominent computer scientist who received the Turing Award in 1971 for his major contributions to the field of Artificial Intelligence. ... In philosophy and AI, the qualification problem is concerned with the impossibility of listing all the preconditions required for a real-world action to have its intended effect. ... In artificial intelligence, the term situated refers to an agent which is embedded in an environment. ... Computational intelligence (CI) is a branch of artificial intelligence. ... Cyc is an artificial intelligence project that attempts to assemble a comprehensive ontology and database of everyday common sense knowledge, with the goal of enabling AI applications to perform human-like reasoning. ...

Planning

Main article: automated planning and scheduling

Intelligent agents must be able set goals and achieve them.^[38] 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. There are several types of planning problems: Automated planning and scheduling is a branch of artificial intelligence that concerns the realisation of strategies or action sequences, typically for execution by intelligent agents, autonomous robots and unmanned vehicles. ...

• Classical planning problems assume that the agent is the only thing acting on the world, and that the agent can be certain what the consequences of it's actions may be.^[39] Partial order planning problems take into account the fact that sometimes it's not important which sub-goal the agent achieves first.^[40]
• If the environment is changing, or if the agent can't be sure of the results of its actions, it must periodically check if the world matches its predictions (conditional planning and execution monitoring) and it must change its plan as this becomes necessary (replanning and continuous planning).^[41]
• Some planning problems take into account the utility or "usefulness" of a given outcome. These problems can be analyzed using tools drawn from economics, such as decision theory or decision analysis^[42] and information value theory.^[43]
• Multi-agent planning problems try to determine the best plan for a community of agents, using cooperation and competition to achieve a given goal.^[44] These problems are related emerging fields like evolutionary algorithms and swarm intelligence.

In mathematics, a partially ordered set (or poset for short) is a set equipped with a special binary relation which formalizes the intuitive concept of an ordering. ... Automated planning and scheduling is a branch of artificial intelligence that concerns the realisation of strategies or action sequences, typically for execution by intelligent agents, autonomous robots and unmanned vehicles. ... In economics, utility is a measure of the relative happiness or satisfaction (gratification) gained. ... Economics (deriving from the Greek words οίκω [okos], house, and νέμω [nemo], rules hence household management) is the social science that studies the allocation of scarce resources to satisfy unlimited wants. ... Decision theory is an area of study of discrete mathematics that models human decision-making in science, engineering and indeed all human social activities. ... Decision analysis (DA) is the discipline comprising the philosophy, theory, methodology, and professional practice necessary to address important decisions in a formal manner. ... The creator of or main contributor to this page may have a conflict of interest with the subject of this article. ... In computer science, agents in a multi-agent system need to coordinate their actions. ... Look up agent in Wiktionary, the free dictionary. ... This article is about cooperation as used in the social sciences. ... Competition is the act of striving against others for the purpose of achieving gain, such as income, pride, amusement, or dominance. ... In artificial intelligence, an evolutionary algorithm (EA) is a subset of evolutionary computation, a generic population-based metaheuristic optimization algorithm. ... Swarm intelligence (SI) is an artificial intelligence technique based around the study of collective behavior in decentralized, self-organized systems. ...

Learning

Main article: machine learning

As a broad subfield of artificial intelligence, machine learning is concerned with the design and development of algorithms and techniques that allow computers to learn. At a general level, there are two types of learning: inductive, and deductive. ...

Natural language processing

Main article: natural language processing

Natural language processing^[45] gives machines the ability to be read and understand the languages human beings speak. The problem of natural language processing involves such subproblems as syntax and parsing,^[46] semantics and disambiguation,^[47] and discourse understanding. (e.g., identifying the speech act, using coherence relations in the text, and deciphering the speaker's intentions or pragmatics.)^[48] 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. 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. ... Natural language processing (NLP) is a subfield of artificial intelligence and computational linguistics. ... For other uses, see Syntax (disambiguation). ... An example of parsing a mathematical expression. ... The introduction to this article provides insufficient context for those unfamiliar with the subject matter. ... “WSD” redirects here. ... The notion speech act is a technical term in linguistics and the philosophy of language. ... Coherence in linguistics is what makes a text semantically meaningful. ... Pragmatics is the study of the ability of natural language speakers to communicate more than that which is explicitly stated. ...

Some straightforward applications of natural language processing include information retrieval (or text mining) and machine translation.^[49] Information retrieval (IR) is the science of searching for information in documents, searching for documents themselves, searching for metadata which describe documents, or searching within databases, whether relational stand-alone databases or hypertextually-networked databases such as the World Wide Web. ... Text mining, sometimes alternately referred to as text data mining, refers generally to the process of deriving high quality information from text. ... Machine translation, sometimes referred to by the acronym MT, is a sub-field of computational linguistics that investigates the use of computer software to translate text or speech from one natural language to another. ...

Perception

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

Machine perception concerns the building of machines that sense and interpret their environments. ... Computer vision is the science and technology of machines that see. ... Speech recognition (in many contexts also known as automatic speech recognition, computer speech recognition or erroneously as voice recognition) is the process of converting a speech signal to a sequence of words in the form of digital data, by means of an algorithm implemented as a computer program. ...

Motion and manipulation

Main article: robotics

The Shadow robot hand system holding a lightbulb. ...

Social intelligence

Main article: affective computing

Emotion and social skills play two roles for an intelligent agent:^[50] Affective computing is computing that deals with the attempt to make machines which can detect and respond to human emotion. ...

• It must be able 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 model human emotions and the perceptual skills to detect emotions.)
• For good human-computer interaction, an intelligent machine also to needs to display emotions — at the very least it must appear polite and sensitive to the humans it interacts with. At best, it should appear to have normal emotions itself.

Game theory is a branch of applied mathematics that is often used in the context of economics. ... Decision theory is an area of study of discrete mathematics that models human decision-making in science, engineering and indeed all human social activities. ... // Human–computer interaction (HCI), alternatively man–machine interaction (MMI) or computer–human interaction (CHI)This interactive computer allows the user to intergrate a reaction towards oneself and the primary source that is the http server, the port and Ip address show as the user connects to the imb harddrive , is...

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.^[8] A few believe that anthropomorphic features like artificial consciousness or an artificial brain may be required for such a project. For the strong AI hypothesis, see philosophy of artificial intelligence Strong AI is a term used by futurists, science fiction writers and forward looking researchers to describe artificial intelligence that matches or exceeds human intelligence. ... AI-complete is, by analogy to NP-completeness in complexity theory, a term first coined by Fanya S. Montalvo to indicate that the difficulty of a computational problem is equivalent to solving the central Artificial Intelligence problem, i. ... For the strong AI hypothesis, see philosophy of artificial intelligence Strong AI is a term used by futurists, science fiction writers and forward looking researchers to describe artificial intelligence that matches or exceeds human intelligence. ... Anthropomorphism, also referred to as personification or prosopopeia, is the attribution of human characteristics to inanimate objects, animals, forces of nature, and others. ... Artificial consciousness (AC), also known as machine consciousness (MC) or synthetic consciousness, is a field related to artificial intelligence and cognitive robotics whose aim is to define that which would have to be synthesized were consciousness to be found in an engineered artifact. ... Artificial brain is the research to develop hardware that has cognitive abilities similar to the human brain. ...

Many of the problems above are considered AI-complete: to solve one problem, you must solve them all. For example, even a straight-forward, limited and specific task like machine translation is AI complete. To translate accurately, a machine must be able to understand the text. It must be able to follow the author's argument, so it must have some ability to reason. It must have extensive world knowledge so that it knows what is being discussed — it must at least be familiar with all the same commonsense facts that the average human translator knows. Some of this knowledge is in the form of facts that can be explicitly represented, but some knowledge is unconscious and closely tied to the human body: for example, the machine may need to understand how an ocean makes one feel to accurately translate a specific metaphor in the text. It must also model the authors' goals, intentions, and emotional states to accurately reproduce them in a new language. In short, the machine is required to have wide variety of human intellectual skills, including reasoning, commonsense knowledge and the intuitions that underly motion and manipulation, perception, and social intelligence. Machine translation, therefore, is believed to be AI-complete: it may require strong AI to be done as well as humans can do it.^[51] AI-complete is, by analogy to NP-completeness in complexity theory, a term first coined by Fanya S. Montalvo to indicate that the difficulty of a computational problem is equivalent to solving the central Artificial Intelligence problem, i. ... Machine translation, sometimes referred to by the acronym MT, is a sub-field of computational linguistics that investigates the use of computer software to translate text or speech from one natural language to another. ... Understanding is a psychological state in relation to an object or person whereby one is able to think about it and use concepts to be able to deal adequately with that object. ... Machine translation, sometimes referred to by the acronym MT, is a sub-field of computational linguistics that investigates the use of computer software to translate text or speech from one natural language to another. ... AI-complete is, by analogy to NP-completeness in complexity theory, a term first coined by Fanya S. Montalvo to indicate that the difficulty of a computational problem is equivalent to solving the central Artificial Intelligence problem, i. ... For the strong AI hypothesis, see philosophy of artificial intelligence Strong AI is a term used by futurists, science fiction writers and forward looking researchers to describe artificial intelligence that matches or exceeds human intelligence. ...

Approaches to AI

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. 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. Many of these researchers gathered for meetings of the Teleological Society at Princeton and the Ratio Club in England.^[52] Neurology is a branch of medicine dealing with disorders of the nervous system. ... Not to be confused with information technology, information science, or informatics. ... For other uses, see Cybernetics (disambiguation). ... W. Grey Walter (February 19, 1910 - 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 Anglo-American researcher William Grey Walter) and used in computer science and mechanical engineering training. ... The Johns Hopkins Beast was an early robot built in the 1960 at Johns Hopkins University. ... The Ratio Club was a small informal dining club of young psychologists, physiologists, mathematicians and engineers who met to discuss issues in cybernetics. ...

Traditional symbolic AI

When access to digital computers became possible in the middle 1950s, AI research began explore that 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 it's own style of research. John Haugeland named these approaches to AI "good old fashioned AI" or "GOFAI".^[53] CMU is an acronym for three different universities: Carnegie Mellon University in Pittsburgh, Pennsylvania Central Michigan University in Mount Pleasant, Michigan Chiang Mai University in Chiangmai, Thailand Central Michigan University claims CMU as a trademark: [1]. A search through the United States Patent and Trademark Offices trademark database will... Stanford may refer: Stanford University Places: Stanford, Kentucky Stanford, California, home of Stanford University Stanford Shopping Center Stanford, New York, town in Dutchess County. ... Mapúa Institute of Technology (MIT, MapúaTech or simply Mapúa) is a private, non-sectarian, Filipino tertiary institute located in Intramuros, Manila. ... John Haugeland (born in 1945), is a philosopher and Professor of Philosophy at the University of Chicago. ... GOFAI stands for Good Old Fashioned Artificial Intelligence. ...

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. Their research team performed psychological experiments to demonstrate the similarities between human problem solving and the programs (such as their "General Problem Solver") they where developing. This tradition, centered at Carnegie Mellon University,^[54] would eventually culminate in the development of the Soar architecture in the middle 80s.^[55]

Logical AI 

Unlike Newell and Simon, John McCarthy felt that machines did not need to simulate human thought, but should instead try find the essence of abstract reasoning and problem solving, regardless of whether people used the same algorithms.^[56] His laboratory at Stanford (SAIL) focussed on using formal logic to solve wide variety of problems, including knowledge representation, planning and learning. Work in logic led to the development of the programming language Prolog and the science of logic programming.^[57]

"Scruffy" symbolic AI 

In contrast to the formal methods pursued at CMU, Stanford and Edinburgh, the 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 silver bullet, no simple and general principle (like logic) that would capture all the aspects of intelligent behavior. An important realization was that AI required large amounts of commonsense knowledge, and that this had to be engineered one complicated concept at time. This tradition, which Roger Schank named "scruffy AI"^[58] still forms the basis of research into commonsense knowledge, such as Doug Lenat's Cyc.

Knowledge based AI 

When computers with large memories became available around 1970, researchers from all three traditions began to build knowledge into AI applications. This "knowledge revolution" led to the development and deployment of expert systems, the first truly successful form of AI software.^[59]

Alan Greenspan, former chairman, United States Federal Reserve. ... Herbert Alexander Simon (June 15, 1916 – February 9, 2001) was an American political scientist whose research ranged across the fields of cognitive psychology, computer science, public administration, economics, management, and philosophy of science and a professor, most notably, at Carnegie Mellon University. ... Allen Newell (March 19, 1927 - July 19, 1992) was a researcher in computer science and cognitive psychology at the RAND corporation. ... Cognitive science is usually defined as the scientific study either of mind or of intelligence (e. ... Operations Research or Operational Research (OR) is an interdisciplinary branch of mathematics which uses methods like mathematical modeling, statistics, and algorithms to arrive at optimal or good decisions in complex problems which are concerned with optimizing the maxima (profit, faster assembly line, greater crop yield, higher bandwidth, etc) or minima... Management science, or MS, is the discipline of using mathematics, and other analytical methods, to help make better business decisions. ... Psychological science redirects here. ... General Problem Solver (GPS) was a computer program created in 1957 by Herbert Simon and Allen Newell to build a universal problem solver machine. ... Carnegie Mellon University is a private research university in Pittsburgh, Pennsylvania, United States. ... Soar (also known as SOAR) is a symbolic cognitive architecture, created by John Laird, Allen Newell, and Paul Rosenbloom at Carnegie Mellon University. ... Allen Newell (March 19, 1927 - July 19, 1992) was a researcher in computer science and cognitive psychology at the RAND corporation. ... Herbert Alexander Simon (June 15, 1916 – February 9, 2001) was an American political scientist whose research ranged across the fields of cognitive psychology, computer science, public administration, economics, management, and philosophy of science and a professor, most notably, at Carnegie Mellon University. ... John McCarthy (born September 4, 1927, in Boston, Massachusetts, sometimes known affectionately as Uncle John McCarthy), is a prominent computer scientist who received the Turing Award in 1971 for his major contributions to the field of Artificial Intelligence. ... Stanford redirects here. ... The Stanford Artificial Intelligence Laboratory (commonly called the Stanford AI Lab, or SAIL), was one of the leading centres for artificial intelligence research from the 1960s through the 1980s. ... Logic (from Classical Greek λόγος logos; meaning word, thought, idea, argument, account, reason, or principle) is the study of the principles and criteria of valid inference and demonstration. ... Knowledge representation is an issue that arises in both cognitive science and artificial intelligence. ... Automated planning and scheduling is a branch of artificial intelligence that concerns the realisation of strategies or action sequences, typically for execution by intelligent agents, autonomous robots and unmanned vehicles. ... As a broad subfield of artificial intelligence, machine learning is concerned with the design and development of algorithms and techniques that allow computers to learn. At a general level, there are two types of learning: inductive, and deductive. ... Prolog is a logic programming language. ... Logic programming (which might better be called logical programming by analogy with mathematical programming and linear programming) is, in its broadest sense, the use of mathematical logic for computer programming. ... CMU is an acronym for three different universities: Carnegie Mellon University in Pittsburgh, Pennsylvania Central Michigan University in Mount Pleasant, Michigan Chiang Mai University in Chiangmai, Thailand Central Michigan University claims CMU as a trademark: [1]. A search through the United States Patent and Trademark Offices trademark database will... Stanford may refer: Stanford University Places: Stanford, Kentucky Stanford, California, home of Stanford University Stanford Shopping Center Stanford, New York, town in Dutchess County. ... For other uses, see Edinburgh (disambiguation). ... Mapúa Institute of Technology (MIT, MapúaTech or simply Mapúa) is a private, non-sectarian, Filipino tertiary institute located in Intramuros, Manila. ... Marvin Lee Minsky (born August 9, 1927), sometimes affectionately known as Old Man Minsky, is an American cognitive scientist in the field of artificial intelligence (AI), co-founder of MITs AI laboratory, and author of several texts on AI and philosophy. ... Seymour Papert Seymour Papert (born March 1, 1928 Pretoria, South Africa) is an MIT mathematician, computer scientist, and prominent educator. ... 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 (from Classical Greek λόγος logos; meaning word, thought, idea, argument, account, reason, or principle) is the study of the principles and criteria of valid inference and demonstration. ... Commonsense reasoning is the branch of Artificial intelligence concerned with replicating human thinking. ... 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 holy wars in artificial intelligence research. ... Commonsense reasoning is the branch of Artificial intelligence concerned with replicating human thinking. ... Douglas B. Lenat is the CEO of Cycorp, Inc. ... Cyc is an artificial intelligence project that attempts to assemble a comprehensive ontology and database of everyday common sense knowledge, with the goal of enabling AI applications to perform human-like reasoning. ... Knowledge representation is an issue that arises in both cognitive science and artificial intelligence. ... An expert system, also known as a knowledge based system, is a computer program that contains the knowledge and analytical skills of one or more human experts, related to a specific subject. ...

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.^[60] 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. A number of researchers began to look into "sub-symbolic" approaches to specific AI problems.^[61] For other uses, see Cybernetics (disambiguation). ... // Traditionally, the term neural network had been used to refer to a network or circuitry of biological neurons. ... Machine perception concerns the building of machines that sense and interpret their environments. ... The Shadow robot hand system holding a lightbulb. ... As a broad subfield of artificial intelligence, machine learning is concerned with the design and development of algorithms and techniques that allow computers to learn. At a general level, there are two types of learning: inductive, and deductive. ... Pattern recognition is a field within the area of machine learning. ...

Bottom-up, situated, behavior based or nouvelle AI 

Researchers from the related field of