Inconsistency and Accuracy of Heuristics with A* Search
Hang Dinh, Hieu Dinh

TL;DR
This paper investigates the relationship between heuristic inconsistency and accuracy in A* search, revealing that more accurate heuristics often exhibit higher inconsistency and improve search efficiency.
Contribution
It provides the first analysis linking heuristic inconsistency and accuracy, supported by theoretical insights and empirical experiments on the Knapsack problem.
Findings
More accurate heuristics tend to be more inconsistent.
Increased inconsistency can lead to fewer node expansions.
The correlation between accuracy and inconsistency impacts A* performance.
Abstract
Many studies in heuristic search suggest that the accuracy of the heuristic used has a positive impact on improving the performance of the search. In another direction, historical research perceives that the performance of heuristic search algorithms, such as A* and IDA*, can be improved by requiring the heuristics to be consistent -- a property satisfied by any perfect heuristic. However, a few recent studies show that inconsistent heuristics can also be used to achieve a large improvement in these heuristic search algorithms. These results leave us a natural question: which property of heuristics, accuracy or consistency/inconsistency, should we focus on when building heuristics? While there are studies on the heuristic accuracy with the assumption of consistency, no studies on both the inconsistency and the accuracy of heuristics are known to our knowledge. In this study, we…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsMetaheuristic Optimization Algorithms Research · Optimization and Search Problems · Constraint Satisfaction and Optimization
