Symbolic AI

Alan Turing (1912–1954) was a British mathematician whose 1936 paper defined computation with an abstract machine. His 1950 paper proposed the imitation game, now called the Turing test, and he is counted among the founders of artificial intelligence.

John McCarthy (1927–2011) was an American computer scientist. His 1955 proposal is credited with coining the term “artificial intelligence”, he organised the 1956 Dartmouth workshop, and he created the LISP programming language.

Alan Turing's 1936 paper defined computable numbers through an abstract machine, now called the Turing machine, and showed that no general method can decide whether any given mathematical statement is provable.

In 1943 Warren McCulloch and Walter Pitts described a simplified model of a neuron and showed that networks of such units can carry out logical reasoning, an early link between brain models and computation.

The Turing test is Alan Turing's 1950 proposal for replacing the question "Can machines think?" with a game: a machine passes if an interrogator cannot tell its written answers apart from a human's.

In 1950 Alan Turing replaced the question "Can machines think?" with the imitation game, now called the Turing test, and answered the main objections to machine intelligence one by one.

Logic Theorist, completed in 1956 by Allen Newell, Herbert A. Simon and Cliff Shaw, was the first program deliberately built to perform automated reasoning; it proved dozens of theorems from Principia Mathematica and introduced heuristics, list processing and reasoning as search.

Lisp is a programming language invented by John McCarthy at MIT in 1958, whose programs are themselves lists. It became the favoured language of early artificial intelligence research and introduced automatic garbage collection.

John McCarthy's 1959 paper proposing the advice taker, a program that would solve problems by manipulating sentences in formal languages and act when it deduced an imperative — an early statement of logical AI.

A. L. Samuel's 1959 paper reporting experiments in which a checkers program, given only the rules of the game and an imperfect set of parameters, learned in 8 to 10 hours of playing time to beat the person who wrote it.

Marvin Minsky's 1961 survey in Proceedings of the IRE organized heuristic programming into five problem areas — search, pattern recognition, learning, planning and induction — and argued that machines would need to build models of their environments.

DENDRAL was a Stanford artificial intelligence project begun in 1964 that identified unknown organic molecules from mass spectra using chemical knowledge. It is widely described as the first expert system and the ancestor of later systems such as MYCIN and PROSPECTOR.

Shakey was a mobile robot built at SRI International between 1966 and 1972, the first AI-based mobile robot that could perceive and reason about its surroundings and act without step-by-step instructions. Its project produced the A* search algorithm and the STRIPS planning system.

A 1969 book by Marvin Minsky and Seymour Papert that proved mathematical limits on what single-layer perceptrons can compute — notably that they cannot compute parity or connectedness — and has long been credited with steering research away from neural networks.

AI winter is a period of sharply reduced funding and interest in artificial intelligence research. The field's hype cycles have produced two such downturns, usually dated to about 1974–1980 and 1987–2000.

IBM's chess computer that in May 1997 became the first computer system to defeat a reigning world chess champion in a match under standard tournament time controls.

MYCIN was an early expert system built at Stanford in the 1970s to identify bacteria causing severe infections and recommend antibiotic treatment, notable for separating its rule base from its inference engine and for explaining its own reasoning.

A private Ivy League college in Hanover, New Hampshire, founded by royal charter in 1769. Its 1956 summer research project, proposed by John McCarthy, is credited with launching artificial intelligence as a field.

MIT, the Massachusetts Institute of Technology in Cambridge, Massachusetts, hosted the AI lab that Marvin Minsky and John McCarthy co-founded, which later became CSAIL. The lab also invented Lisp machines, and Minsky co-wrote the book Perceptrons.

Stanford University is a private research university in California, home to the Stanford AI Lab (SAIL) and the Institute for Human-Centered AI, which publishes the AI Index.

Carnegie Mellon University in Pittsburgh has one of the earliest US computer science departments. Its researchers built the Logic Theorist, Sphinx speech recognition and the Deep Blue lineage, and won the 2007 DARPA Urban Challenge.

Herbert A. Simon (1916–2001) was a political scientist, psychologist and computer scientist who, with Allen Newell and J. C. Shaw, built the first successful AI program and later received the Nobel Prize in Economics.

Berlin-born American computer scientist who wrote ELIZA, an early program that held a written conversation with a user, and later published an influential critique of artificial intelligence.

American computer scientist and psychologist who, with Herbert A. Simon and J. C. Shaw, built the first list-processing language and the earliest heuristic problem-solving programs, treating thought as computation.

Marvin Minsky (1927–2016) was an American scientist who co-founded MIT’s AI laboratory and co-signed the 1955 Dartmouth proposal. With Seymour Papert he wrote the 1969 book Perceptrons, which analysed the limits of simple neural networks.

Edward Feigenbaum (born 1936) is known as the father of expert systems. His projects produced DENDRAL, META-DENDRAL, MYCIN and ONCOCIN, he pioneered the term "knowledge engineering", and he shared the 1994 ACM Turing Award.

IBM Research built Deep Blue, which beat world chess champion Garry Kasparov in 1997, and Watson, which won Jeopardy! in 2011. Nathaniel Rochester of IBM was also one of the four signatories of the 1955 Dartmouth proposal.

GPS was a program built at RAND to act as a universal problem-solving machine, and is credited as the first computer program to separate problem knowledge from a general solving strategy.

A checkers program built by Arthur Samuel at IBM, begun in 1949 and published in 1959, that learned by memorising positions, playing itself and scoring board positions, and played at a respectable amateur level.

MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL), formed in 2003 by merging the MIT AI Lab with the Laboratory for Computer Science, is the largest laboratory on the MIT campus.

The Stanford Artificial Intelligence Laboratory, started by John McCarthy in 1963, is associated with the Stanford arm robot design, the Stanley self-driving car and the SAIL programming language.

ELIZA is an early program for holding a natural-language conversation with a computer, built at MIT by Joseph Weizenbaum in the mid-1960s. Its DOCTOR script imitated a psychotherapist, and the readiness of users to treat it as understanding became known as the ELIZA effect.

A January 1966 paper by Joseph Weizenbaum presenting ELIZA, a program on MIT's MAC time-sharing system that used keyword-triggered decomposition and reassembly rules to enable certain natural-language conversations between people and computers.

The Department of Machine Intelligence and Perception at the University of Edinburgh, created in October 1966 out of Donald Michie's Experimental Programming Unit, was an early British institutional home for artificial intelligence and a forerunner of the university's School of Informatics.

The MIT Artificial Intelligence Laboratory, formed in 1970 under Marvin Minsky, grew out of MIT's earlier AI group inside Project MAC; in 2003 it merged with the Laboratory for Computer Science to form CSAIL.

SHRDLU was an early natural-language program built by Terry Winograd at MIT in 1968–1970 that conversed in English about a small blocks world, executing commands, answering questions and learning names — a landmark demo whose success fed an optimism later systems could not sustain.

R1, known inside Digital Equipment Corporation as XCON, was a rule-based expert system written by John P. McDermott at Carnegie Mellon University in 1978 to configure VAX computer orders automatically.

Cyc is a hand-built knowledge base and ontology of common-sense knowledge, begun by Douglas Lenat in 1984 to give software the basic concepts and rules about how the world works.

CALO was SRI's cognitive assistant project, begun in 2003 as part of a five-year, 150 million dollar DARPA program, built to learn from observation rather than fixed programming. Its work on virtual personal assistants was later leveraged to create Siri.

Planning in AI agents is the process of breaking a goal into intermediate steps, choosing actions, and revising the plan as results arrive, rather than producing an answer in one pass.[^1][^2]

Chinook is a checkers-playing computer program built by Jonathan Schaeffer and colleagues [^1]. It became the first computer program to win a human world championship in any game, and its completed form cannot be beaten [^1].

SRI International is a non-profit research institute in Menlo Park, California, founded in 1946 as the Stanford Research Institute. Its AI Center built Shakey the robot, and its later work led to Siri.

American electrical engineer who built one of the first checkers-playing programs and, in a 1959 paper, helped name the field now called machine learning.

Zhang Bo (born 1935) is a scholar in automatic control and artificial intelligence. He studied and taught at Tsinghua University and helped found the State Key Laboratory of Intelligent Technology and Systems.

AAAI is an international nonprofit scientific society for artificial intelligence, founded in 1979, which runs a flagship annual conference and has published a quarterly magazine since 1980.

AlphaGeometry is a Google DeepMind system that pairs a neural language model with a symbolic deduction engine to solve olympiad geometry problems, reaching near gold-medal level on a benchmark of 30 problems.

AlphaProof is a Google DeepMind reinforcement-learning system that proves mathematical statements in the formal language Lean. At the 2024 International Mathematical Olympiad it solved three problems, and together with AlphaGeometry 2 reached silver-medal level.