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The Stanford Research Institute Problem Solver, known by its acronym STRIPS, is an automated planner developed by Richard Fikes and Nils Nilsson in 1971 at SRI International. [1] The same name was later used to refer to the formal language of the inputs to this planner. This language is the base for most of the languages for expressing ...
General Problem Solver. General Problem Solver (GPS) is a computer program created in 1957 by Herbert A. Simon, J. C. Shaw, and Allen Newell (RAND Corporation) intended to work as a universal problem solver machine. In contrast to the former Logic Theorist project, the GPS works with means–ends analysis.
In 2022, OpenAI created a neural network-based theorem prover for Lean, which used a language model to generate proofs of various high-school-level olympiad problems. [ 17 ] Later that year, Meta AI created an AI model that has solved 10 International Mathematical Olympiad problems; this model is available for public use with the Lean environment.
Simon was a pioneer in the field of artificial intelligence, creating with Allen Newell the Logic Theory Machine (1956) and the General Problem Solver (GPS) (1957) programs. GPS may possibly be the first method developed for separating problem solving strategy from information about particular problems.
Gurobi Optimizer is a prescriptive analytics platform and a decision-making technology developed by Gurobi Optimization, LLC. The Gurobi Optimizer (often referred to as simply, “Gurobi”) is a solver, since it uses mathematical optimization to calculate the answer to a problem. Gurobi is included in the Q1 2022 inside BIGDATA “Impact 50 ...
Logic Theorist is a computer program written in 1956 by Allen Newell, Herbert A. Simon, and Cliff Shaw. [1] It was the first program deliberately engineered to perform automated reasoning, and has been described as "the first artificial intelligence program". [1][a] Logic Theorist proved 38 of the first 52 theorems in chapter two of Whitehead ...
Constraint satisfaction problem. Constraint satisfaction problems (CSPs) are mathematical questions defined as a set of objects whose state must satisfy a number of constraints or limitations. CSPs represent the entities in a problem as a homogeneous collection of finite constraints over variables, which is solved by constraint satisfaction ...
e. In artificial intelligence, symbolic artificial intelligence (also known as classical artificial intelligence or logic-based artificial intelligence) [1][2] is the term for the collection of all methods in artificial intelligence research that are based on high-level symbolic (human-readable) representations of problems, logic and search. [3]
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