Abstract
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.
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Hayashi, H., Tokura, S., Hasegawa, T., Ozaki, F. (2006). Dynagent: An Incremental Forward-Chaining HTN Planning Agent in Dynamic Domains. In: Baldoni, M., Endriss, U., Omicini, A., Torroni, P. (eds) Declarative Agent Languages and Technologies III. DALT 2005. Lecture Notes in Computer Science(), vol 3904. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11691792_11
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DOI: https://doi.org/10.1007/11691792_11
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