Tractable Cost-Optimal Planning over Restricted Polytree Causal Graphs
2015 (English)In: Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015Conference paper (Refereed)
Causal graphs are widely used to analyze the complexity of planning problems. Many tractable classes have been identified with their aid and state-of-the-art heuristics have been derived by exploiting such classes. In particular, Katz and Keyder have studied causal graphs that are hourglasses (which is a generalization of forks and inverted-forks) and shown that the corresponding cost-optimal planning problem is tractable under certain restrictions. We continue this work by studying polytrees (which is a generalization of hourglasses) under similar restrictions. We prove tractability of cost-optimal planning by providing an algorithm based on a novel notion of variable isomorphism. Our algorithm also sheds light on the k-consistency procedure for identifying unsolvable planning instances. We speculate that this may, at least partially, explain why merge-and-shrink heuristics have been successful for recognizing unsolvable instances.
Place, publisher, year, edition, pages
automated planning, causal graph, polynomial-time algorithm, cost-optimal planning, polytree
IdentifiersURN: urn:nbn:se:liu:diva-118729ISBN: 978-1-57735-703-2OAI: oai:DiVA.org:liu-118729DiVA: diva2:816591
29th AAAI Conference on Artificial Intelligence (AAAI-15), January 25–30, Austin, TX, USA
FunderCUGS (National Graduate School in Computer Science)