Planning with incomplete information

  • Authors:
  • Hector Geffner

  • Affiliations:
  • ICREA & Universitat Pompeu Fabra, Barcelona, Spain

  • Venue:
  • MoChArt'10 Proceedings of the 6th international conference on Model checking and artificial intelligence
  • Year:
  • 2010

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Abstract

Planning is concerned with the development of solvers for a wide range of models where actions must be selected for achieving goals. In these models, actions may be deterministic or not, and full or partial sensing may be available. In the last few years, significant progress has been made, resulting in algorithms that can produce plans effectively in a variety of settings. These developments have to do with new formulations, inference techniques, and transformations. In this paper, I review some of these developments, focusing on those pertaining to planning with incomplete information.