Computer Science – Artificial Intelligence
Scientific paper
2006-09-19
LMCS 2 (4:2) 2006
Computer Science
Artificial Intelligence
34 pages, 7 Figures
Scientific paper
10.2168/LMCS-2(4:2)2006
We present a state-based regression function for planning domains where an agent does not have complete information and may have sensing actions. We consider binary domains and employ a three-valued characterization of domains with sensing actions to define the regression function. We prove the soundness and completeness of our regression formulation with respect to the definition of progression. More specifically, we show that (i) a plan obtained through regression for a planning problem is indeed a progression solution of that planning problem, and that (ii) for each plan found through progression, using regression one obtains that plan or an equivalent one.
Baral Chitta
Son Tran Cao
Tuan Le-Chi
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