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PDDL+ Planning with Hybrid Automata: Foundations of Translating Must Behavior

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Bogomolov, Sergiy
Magazzeni, Daniele
Minopoli, Stefano
Wehrle, Martin

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Association for the Advancement of Artificial Intelligence (AAAI)

Abstract

Planning in hybrid domains poses a special challenge due to the involved mixed discrete-continuous dynamics. A recent solving approach for such domains is based on applying model checking techniques on a translation of PDDL+ planning problems to hybrid automata. However, the proposed translation is limited because must behavior is only overapproximated, and hence, processes and events are not re- flected exactly. In this paper, we present the theoretical foundation of an exact PDDL+ translation. We propose a schema to convert a hybrid automaton with must transitions into an equivalent hybrid automaton featuring only may transitions.

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Proceedings of the Twenty-Sixth International Conference on Automated Planning and Scheduling (ICAPS 2016)

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Open Access

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