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Algorithmic knowledge

Published: 13 March 1994 Publication History

Abstract

The standard model of knowledge in multi-agent systems suffers from what has been called the <i>logical omniscience problem:</i> agents know all tautologies, and know all the logical consequences of their knowledge. For many types of analysis, this turns out not to be a problem. Knowledge is viewed as being <i>ascribed</i> by the system designer to the agents; agents are not assumed to compute their knowledge in any way, nor is it assumed that they can necessarily answer questions based on their knowledge. Nevertheless, in many applications that we are interested in, agents need to <i>act</i> on their knowledge. In such applications, an externally ascribed notion of knowledge is insufficient: clearly an agent can base his actions only on what he <i>explicitly</i> knows. Furthermore, an agent that has to act on his knowledge has to be able to compute this knowledge; we do need to take into account the algorithms available to the agent, as well as the "effort" required to compute knowledge. In this paper, we show how the standard model can be modified in a natural way to take the computational aspects of knowledge into account.

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    Published In

    cover image Guide Proceedings
    TARK '94: Proceedings of the 5th conference on Theoretical aspects of reasoning about knowledge
    March 1994
    348 pages
    ISBN:155860331X
    • Editor:
    • Ronald Fagin

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    Morgan Kaufmann Publishers Inc.

    San Francisco, CA, United States

    Publication History

    Published: 13 March 1994

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    Overall Acceptance Rate 61 of 177 submissions, 34%

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    • (2007)Dealing with logical omniscienceProceedings of the 11th conference on Theoretical aspects of rationality and knowledge10.1145/1324249.1324273(169-176)Online publication date: 25-Jun-2007
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