A Planning Graph Heuristic for Forward-Chaining Adversarial Planning

A Planning Graph Heuristic for Forward-Chaining Adversarial Planning. Bercher, P. & Mattmüller, R. Technical Report 238, University of Freiburg, Germany, 7, 2008.

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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 report, we investigate a forward-chaining 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.

@techreport{Bercher2008FONDPGHeuristicTR,
  author         = {Pascal Bercher and Robert Mattm{\"u}ller},
  title          = {A Planning Graph Heuristic for Forward-Chaining Adversarial Planning},
  institution    = {University of Freiburg, Germany},
  year           = {2008},
  number         = {238},
  month          = {7},
  abstract       = {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 report, we investigate a forward-chaining 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.},
  url_Paper      = {https://bercher.net/publications/2008/Bercher2008FONDPGHeuristicTR.pdf},
  keywords       = {various}
}

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