Computer Science – Artificial Intelligence
Scientific paper
2009-09-03
Computer Science
Artificial Intelligence
This paper appears in Twelfth International Workshop on Non-Monotonic Reasoning (NMR08). An earlier version of this paper appe
Scientific paper
In this paper, we address the problem of generating preferred plans by combining the procedural control knowledge specified by Hierarchical Task Networks (HTNs) with rich qualitative user preferences. The outcome of our work is a language for specifyin user preferences, tailored to HTN planning, together with a provably optimal preference-based planner, HTNPLAN, that is implemented as an extension of SHOP2. To compute preferred plans, we propose an approach based on forward-chaining heuristic search. Our heuristic uses an admissible evaluation function measuring the satisfaction of preferences over partial plans. Our empirical evaluation demonstrates the effectiveness of our HTNPLAN heuristics. We prove our approach sound and optimal with respect to the plans it generates by appealing to a situation calculus semantics of our preference language and of HTN planning. While our implementation builds on SHOP2, the language and techniques proposed here are relevant to a broad range of HTN planners.
McIlraith Sheila A.
Sohrabi Shirin
No associations
LandOfFree
On Planning with Preferences in HTN does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.
If you have personal experience with On Planning with Preferences in HTN, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and On Planning with Preferences in HTN will most certainly appreciate the feedback.
Profile ID: LFWR-SCP-O-664075