Abstract
The “planning as satisfiability” approach for classical planning establishes a correspondence between planning problems and logical theories, and, consequently, between plans and models. This work proposes a similar framework for contingency planning: considering contingent planning problems where the sources of indeterminism are incomplete knowledge about the initial state, non-inertial fluents and non-deterministic actions, it shows how to encode such problems into Linear Time Logic. Exploiting the semantics of the logic, and the notion of conditioned model introduced in this work, a formal characterization is given of the notion of contingent plan (a plan together with the set of conditions that ensure its executability).
This work has been partially supported by ASI - Agenzia Spaziale Italiana.
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Mayer, M.C., Limongelli, C., Orlandini, A., Poggioni, V. (2003). Planning under Uncertainty in Linear Time Logic. In: Cappelli, A., Turini, F. (eds) AI*IA 2003: Advances in Artificial Intelligence. AI*IA 2003. Lecture Notes in Computer Science(), vol 2829. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-39853-0_27
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DOI: https://doi.org/10.1007/978-3-540-39853-0_27
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