Operator counting heuristics for probabilistic planning
Date
Authors
W. Trevizan, Felipe
Thiebaux, Sylvie
Haslum, Patrik
Journal Title
Journal ISSN
Volume Title
Publisher
AAAI Press
Abstract
For the past 25 years, heuristic search has been used to solve domain-independent probabilistic planning problems, but with heuristics that determinise the problem and ignore precious probabilistic information. In this paper, we present a generalization of the operator-counting family of heuristics to Stochastic Shortest Path problems (SSPs) that is able to represent the probability of the actions outcomes. Our experiments show that the equivalent of the net change heuristic in this generalized framework obtains significant run time and coverage improvements over other state-of-the-art heuristics in different planners.
Description
Citation
Collections
Source
IJCAI International Joint Conference on Artificial Intelligence
Type
Book Title
Entity type
Access Statement
Free Access via publisher website
License Rights
Restricted until
2099-12-31
Downloads
File
Description