Heuristic Search in Cyclic AND / OR Graphs

Eric A. Hansen, Shlomo Zilberstein

Heuristic search algorithms can find solutions that take the form of a simple path (A*), a tree or an acyclic graph (AO*). We present anovel generalization of heuristic search (called LAO*) that can find solutions with loops, that is, solutions that take the form of a cyclic graph. We show that it can be used to solve Markov decision problems without evaluating the entire state space, giving it an advantage over dynamic-programming algorithms such as policy iteration and value iteration as an approach to stochastic planning.


This page is copyrighted by AAAI. All rights reserved. Your use of this site constitutes acceptance of all of AAAI's terms and conditions and privacy policy.