Anthropomorphic Self-Models for Metareasoning Agents

Andrew S. Gordon, Jerry R. Hobbs, Michael T. Cox

Representations of an AI agent's mental states and processes are necessary to enable metareasoning, i.e. thinking about thinking. However, the formulation of suitable representations remains an outstanding AI research challenge, with no clear consensus on how to proceed. This paper outlines an approach involving the formulation of anthropomorphic self-models, where the representations that are used for metareasoning are based on formalizations of commonsense psychology. We describe two research activities that support this approach, the formalization of broad-coverage commonsense psychology theories and use of representations in the monitoring and control of object-level reasoning. We focus specifically on metareasoning about memory, but argue that anthropomorphic self-models support the development of integrated, reusable, broad-coverage representations for use in metareasoning systems.

Subjects: 11. Knowledge Representation; 7.2 Software Agents

Submitted: May 2, 2008


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