Principles of artificial intelligence
Principles of artificial intelligence
Heuristic search in cyclic AND/OR graphs
AAAI '98/IAAI '98 Proceedings of the fifteenth national/tenth conference on Artificial intelligence/Innovative applications of artificial intelligence
Artificial Intelligence - Special issue on heuristic search in artificial intelligence
Weak, strong, and strong cyclic planning via symbolic model checking
Artificial Intelligence - special issue on planning with uncertainty and incomplete information
The FF planning system: fast plan generation through heuristic search
Journal of Artificial Intelligence Research
Planning graph heuristics for belief space search
Journal of Artificial Intelligence Research
Fast planning through planning graph analysis
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 2
Solving fully-observable non-deterministic planning problems via translation into a general game
KI'09 Proceedings of the 32nd annual German conference on Advances in artificial intelligence
Solving non-deterministic planning problems with pattern database heuristics
KI'09 Proceedings of the 32nd annual German conference on Advances in artificial intelligence
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In contrast to classical planning, in adversarial planning, the planning agent has to face an adversary trying to prevent him from reaching his goals. In this paper, we investigate a forwardchaining approach to adversarial planning based on the AO* algorithm. The exploration of the underlying AND/OR graph is guided by a heuristic evaluation function, inspired by the relaxed planning graph heuristic used in the FF planner. Unlike FF, our heuristic uses an adversarial planning graph with distinct proposition and action layers for the protagonist and antagonist. First results suggest that in certain planning domains, our approach yields results competitive with the state of the art.