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Formal theories of knowledge in AI and robotics

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Abstract

Although the concept ofknowledge plays a central role in artificial intelligence, the theoretical foundations of knowledge representation currently rest on a very limited conception of what it means for a machine to know a proposition. In the current view, the machine is regarded as knowing a fact if its state either explicitly encodes the fact as a sentence of an interpreted formal language or if such a sentence can be derived from other encoded sentences according to the rules of an appropriate logical system. We contrast this conception, the interpreted-symbolic-structure approach, with another, the situated-automata approach, which seeks to analyze knowledge in terms of relations between the state of a machine and the state of its environment over time using logic as a metalanguage in which the analysis is carried out.

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Authors and Affiliations

  1. Artificial Intelligence Center, SRI International, 333 Ravenswood Ave., 94025, Menlo Park, Ca., USA

    Stanley J. Rosenschein

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  1. Stanley J. Rosenschein
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Additional information

This work was supported in part by a gift from the Systems Development Foundation and in part by FMC Corporation under Contract 147466 (SRI Project 7390).

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Rosenschein, S.J. Formal theories of knowledge in AI and robotics. NGCO 3, 345–357 (1985). https://doi.org/10.1007/BF03037076

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