TY - JOUR
T1 - Predicting the effectiveness of bidirectional heuristic search
AU - Sturtevant, Nathan R.
AU - Shperberg, Shahaf
AU - Felner, Ariel
AU - Chen, Jingwei
N1 - Funding Information:
We acknowledge the support of CIFAR and the Natural Sciences and Engineering Research Council of Canada (NSERC). This work was also supported by Israel Science Foundation (ISF) grant #844/17 to Ariel Felner and Eyal Shimony, by BSF grant #2017692, by NSF grant #1815660 and by the Frankel center for CS at BGU.
Publisher Copyright:
Copyright © 2020, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved.
PY - 2020/5/29
Y1 - 2020/5/29
N2 - The question of when bidirectional heuristic search outperforms unidirectional heuristic search has been revisited numerous times in the field of Artificial Intelligence. This paper re-addresses the question of when bidirectional search outperforms unidirectional search using an updated theoretical understanding of the problem. We show that a core set of critical states in the state space are the primary factor determining whether a bidirectional search can outperform a unidirectional search and provide simple measures to determine whether a state space and heuristic contains these critical states. We similarly discuss and show the impact that asymmetry in the underlying problem graph has on the performance of bidirectional algorithms. Experimental results show the impact of these factors on whether a problem should be solved using unidirectional or bidirectional search.
AB - The question of when bidirectional heuristic search outperforms unidirectional heuristic search has been revisited numerous times in the field of Artificial Intelligence. This paper re-addresses the question of when bidirectional search outperforms unidirectional search using an updated theoretical understanding of the problem. We show that a core set of critical states in the state space are the primary factor determining whether a bidirectional search can outperform a unidirectional search and provide simple measures to determine whether a state space and heuristic contains these critical states. We similarly discuss and show the impact that asymmetry in the underlying problem graph has on the performance of bidirectional algorithms. Experimental results show the impact of these factors on whether a problem should be solved using unidirectional or bidirectional search.
UR - http://www.scopus.com/inward/record.url?scp=85088524742&partnerID=8YFLogxK
M3 - Conference article
AN - SCOPUS:85088524742
SN - 2334-0835
VL - 30
SP - 281
EP - 290
JO - Proceedings International Conference on Automated Planning and Scheduling, ICAPS
JF - Proceedings International Conference on Automated Planning and Scheduling, ICAPS
T2 - 30th International Conference on Automated Planning and Scheduling, ICAPS 2020
Y2 - 26 October 2020 through 30 October 2020
ER -