Hierarchical Task Networks (HTNs) are a family of
powerful planning algorithms that have been successfully applied to many complex, real-world domains.
However, they are limited to predictable domains.
In this paper we present HOPPER (Hierarchical
Ordered Partial-Plan Executor and Re-planner), a
hierarchical planning agent that produces partial
plans in a similar way to HTNs but can also handle unexpected events in unpredictable domains by
interleaving planning and execution. HOPPER can
detect and recover from unexpected events that invalidate the plan, and it can detect and exploit
unexpected opportunities both serendipitously and by
|Cite as: Wojnar, M. and Andreae, P. (2009). HOPPER: a hierarchical planning agent for unpredictable domains. In Proc. Thirty-Second Australasian Computer Science Conference (ACSC 2009), Wellington, New Zealand. CRPIT, 91. Mans, B., Ed. ACS. 73-81. |
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