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In computer science, in particular in knowledge representation and reasoning and metalogic, the area of automated reasoning is dedicated to understanding different aspects of reasoning. The study of automated reasoning helps produce computer programs that allow computers to reason completely, or nearly completely, automatically.
The Handbook of Automated Reasoning (ISBN 0444508139, 2128 pages) is a collection of survey articles on the field of automated reasoning. Published in June 2001 by MIT Press, it is edited by John Alan Robinson and Andrei Voronkov. Volume 1 describes methods for classical logic, first-order logic with equality and other theories, and induction.
John Alan Robinson (9 March 1930 – 5 August 2016) was a philosopher, mathematician, and computer scientist.He was a professor emeritus at Syracuse University.. Alan Robinson's major contribution is to the foundations of automated theorem proving.
The inference engine is an automated reasoning system that evaluates the current state of the knowledge-base, applies relevant rules, and then asserts new knowledge into the knowledge base. The inference engine may also include abilities for explanation, so that it can explain to a user the chain of reasoning used to arrive at a particular ...
Automated theorem proving (also known as ATP or automated deduction) is a subfield of automated reasoning and mathematical logic dealing with proving mathematical theorems by computer programs. Automated reasoning over mathematical proof was a major motivating factor for the development of computer science .
Download as PDF; Printable version; In other projects Wikidata item; ... Pages in category "Automated reasoning" The following 16 pages are in this category, out of ...
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 and Bertrand Russell's Principia Mathematica, and found new and shorter proofs for some of them. [3]
Correct answers can be filtered from false positives because the system can rely on versions of the correct answer appearing more times in the corpus than incorrect ones. Some question answering systems rely heavily on automated reasoning. [11] [12]