Fair LTL synthesis for non-deterministic systems using strong cyclic planners

  • Authors:

  • Fabio Patrizi;Nir Lipovetzky;Hector Geffner

  • Affiliations:

  • Sapienza University of Rome, Rome, Italy;The University of Melbourne, Melbourne, Australia;ICREA & Univ. Pompeu Fabra, Barcelona, Spain

  • Venue:
  • IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence
  • Year:
  • 2013

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Abstract

We consider the problem of planning in environments where the state is fully observable, actions have non-deterministic effects, and plans must generate infinite state trajectories for achieving a large class of LTL goals. More formally, we focus on the control synthesis problem under the assumption that the LTL formula to be realized can be mapped into a deterministic Büchi automaton. We show that by assuming that action nondeterminism is fair, namely that infinite executions of a nondeterministic action in the same state yield each possible successor state an infinite number of times, the (fair) synthesis problem can be reduced to a standard strong cyclic planning task over reachability goals. Since strong cyclic planners are built on top of efficient classical planners, the transformation reduces the non-deterministic, fully observable, temporally extended planning task into the solution of classical planning problems. A number of experiments are reported showing the potential benefits of this approach to synthesis in comparison with state-of-the-art symbolic methods.