Knowledge-based programs as succinct policies for partially observable domains

Artificial Intelligence(2020)

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摘要
We suggest to express policies for contingent planning by knowledge-based programs (KBPs). KBPs, introduced by Fagin et al. (1995) [32], are high-level protocols describing the actions that the agent should perform as a function of their current knowledge: branching conditions are epistemic formulas that are interpretable by the agent. The main aim of our paper is to show that KBPs can be seen as a succinct language for expressing policies in single-agent contingent planning.
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关键词
Planning under uncertainty,Contingent planning,Epistemic logic,Knowledge-based programs,Belief tracking
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