In this paper, we propose a symbolic planner based on BDDs, which calculates strong and strong cyclic plans for a given non-deterministic input. The efficiency of the planning approach is based on a translation of the non-deterministic planning problems into a two-player turn-taking game, with a set of actions selected by the solver and a set of actions taken by the environment. The formalism we use is a PDDL-like planning domain definition language that has been derived to parse and instantiate general games. This conversion allows to derive a concise description of planning domains with a minimized state vector, thereby exploiting existing static analysis tools for deterministic planning. © 2009 Springer Berlin Heidelberg.
CITATION STYLE
Kissmann, P., & Edelkamp, S. (2009). Solving fully-observable non-deterministic planning problems via translation into a general game. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5803 LNAI, pp. 1–8). https://doi.org/10.1007/978-3-642-04617-9_1
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