Approximate Epistemic Planning with Postdiction as Answer-Set Programming

We propose a history-based approximation of the Possible Worlds Semantics $\mathcal{PWS}$ for reasoning about knowledge and action. A respective planning system is implemented by a transformation of the problem domain to an Answer-Set Program. The novelty of our approach is elaboration tolerant support for postdiction under the condition that the plan existence problem is still solvable in NP, as compared to $\Sigma_2^P$ for non-approximated $\mathcal{PWS}$ of [20]. We demonstrate our planner with standard problems and present its integration in a cognitive robotics framework for high-level control in a smart home.

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