Dynagent: An Incremental Forward-Chaining HTN Planning Agent in Dynamic Domains

  • Hisashi Hayashi
  • Seiji Tokura
  • Tetsuo Hasegawa
  • Fumio Ozaki
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3904)


HTN planning, especially forward-chaining HTN planning, is becoming important in the areas of agents and robotics, which have to deal with the dynamically changing world. Therefore, replanning in “forward-chaining” HTN planning has become an important subject for future study. This paper presents the new agent algorithm that integrates forward-chaining HTN planning, execution, belief updates, and plan modifications. Also, through combination with an A*-like heuristic search strategy, we show that our agent algorithm is effective for the replanning problem of museum tour guide robots, which is similar to the replanning problem of a traveling salesman.


Planning Algorithm Action Execution Protected Condition Plan Execution Action Rule 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Hisashi Hayashi
    • 1
  • Seiji Tokura
    • 2
  • Tetsuo Hasegawa
    • 1
  • Fumio Ozaki
    • 2
  1. 1.Knowledge Media Laboratory, R&D CenterToshiba CorporationKawasakiJapan
  2. 2.Humancentric Laboratory, R&D CenterToshiba CorporationKawasakiJapan

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