Efficient single frontier bidirectional search

The Single Frontier Bi-Directional Search (SBS) framework was recently introduced. A node in SBS corresponds to a pair of states, one from each of the frontiers and it uses front-tofront heuristics. In this paper we present an enhanced version of SBS, called eSBS, where pruning and caching techniques are applied, which significantly reduce both time and memory needs of SBS. We then present a hybrid of eSBS and IDA* which potentially uses only the square root of the memory required by A* but enables to prune many nodes that IDA* would generate. Experimental results show the benefit of our new approaches on a number of domains. Copyright © 2012, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved.