Planning with Temporally Extended Goals using Heuristic Search

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Temporally extended goals (TEGs) refer to properties that must hold over intermediate and/or final states of a plan. Current planners for TEGs prune the search space during planning via goal progression. However, the fastest classical domain-independent planners rely on heuristic search. In this paper we propose a method for planning with propositional TEGs using heuristic search. To this end, we translate an instance of a planning problem with TEGs into an equivalent classical planning problem. With this translation in hand, we exploit heuristic search to determine a plan. We represent TEGs using propositional linear temporal logic which is interpreted over finite sequences of states. Our translation is based on the construction of a nondeterministic finite automaton for the TEG. We prove the correctness of our algorithm and analyze the complexity of the resulting representation. The translator is fully implemented and available. Our approach consistently outperforms existing approaches to planning with TEGs, often by orders of magnitute.