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A Computational Theory of the Use-Mention Distinction in Natural Language
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Detecting, Classifying, and Handling Contradictions in a Large, Dynamic Information Environment
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In: DTIC (2006)
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Abstract:
A new approach to perturbation tolerance was identified -- the Meta-Cognitive Loop (MCL) -- for responding to contradictions and other anomalies in complex settings. Further investigations with MCL included identifying architectural requirements, and applying MCL to various domains including reinforcement learning, common-sense reasoning, and a task-oriented natural-language interface system. A series of experiments empirically demonstrated the efficacy of MCL in improving the perturbation tolerance of certain machine learning techniques, including Q-learning, SARSA and Prioritized Sweeping. Formal metrics were given for measuring the complexity, dynamicity and overall difficulty of test domains, which allow for derivative measures of perturbation tolerance. A semantics was developed for Active Logic -- the underlying logic on which MCL's contradiction handling is based -- in the propositional case.
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Keyword:
*ANOMALIES; *CONTRADICTIONS; *PERTURBATIONS; *REASONING; COGNITION; Cybernetics; DETECTION; Information Science; LEARNING; MACHINE LEARNING; MCL(META-COGNITIVE LOOP); NATURAL LANGUAGE; RULE BASED SYSTEMS; SEMANTICS; TOLERANCE
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URL: http://www.dtic.mil/docs/citations/ADA457343 http://oai.dtic.mil/oai/oai?&verb=getRecord&metadataPrefix=html&identifier=ADA457343
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Language and Logic: Research in the Formalization of Discourse.
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In: DTIC AND NTIS (1996)
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