Formal theories of knowledge in AI and robotics
New Generation Computing
Making believers out of computers
Artificial Intelligence
Knowledge and common knowledge in a distributed environment
Journal of the ACM (JACM)
Reasoning about knowledge
A knowledge-based framework for belief change part I: foundations
TARK '94 Proceedings of the 5th conference on Theoretical aspects of reasoning about knowledge
Knowledge as a tool in motion planning under uncertainty
TARK '94 Proceedings of the 5th conference on Theoretical aspects of reasoning about knowledge
On the axiomatization of qualitative decision criteria
AAAI'97/IAAI'97 Proceedings of the fourteenth national conference on artificial intelligence and ninth conference on Innovative applications of artificial intelligence
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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.