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Towards Action Prediction Using a Mental-Level Model

Ronen I. Brafman, Moshe Tennenholtz

We propose a formal approach to the problem of prediction based on the following steps: First, a mental-level model is constructed based on the agent's previous actions; next, the model is updated to account for any new observations by the agent, and finally, we predict the optimal action w.r.t. the agent's mental state as its next action. This paper formalizes this prediction process. In order to carry out this process, we need to understand how a mental state can be ascribed to an agent and how this mental state should be updated. In [Brafman and Tennenholtz, 1994b], we examined the first stage. Here we investigate a particular update operator and show that its ascription requires making only weak modeling assumptions.

שפת פרסום אנגלית
דפים 2010-2016
כתב עת IJCAI International Joint Conference on Artificial Intelligence
כרך 2
סטטוס פרסום פורסם - 01.01.1995

ASJC Scopus subject areas

Artificial Intelligence
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Link to publication in Scopus