Title
Heuristics as Markov chains
Abstract
Comparing heuristics has been a major issue from the early days of heuristic search. From the very beginning, measures of the accuracy of heuristic functions were strongly based on the number of nodes generated, and they are often still based on it. In this work, an alternative approach is suggested: to model the accuracy of admissible heuristic functions as the probability of the heuristic hill-climbing search algorithm to find the goal state in a number of steps that equals the heuristic value of an arbitrary node. The resulting method serves to assess on the accuracy of both consistent and inconsistent heuristic functions. Comparisons with different sizes of the sliding-tile puzzle show that the model suggested predicts the accuracy of the heuristic function with a good precision. The resulting procedure is used to derive figures on the accuracy of a large number of heuristics for the 15-Puzzle with different variants of the search algorithm IDA.
Year
DOI
Venue
2015
10.1007/s10472-014-9439-1
Annals of Mathematics and Artificial Intelligence
Keywords
DocType
Volume
Heuristic search,Accuracy of heuristic functions,N-puzzle,68T20
Journal
73
Issue
ISSN
Citations 
3-4
1012-2443
0
PageRank 
References 
Authors
0.34
5
1
Name
Order
Citations
PageRank
Carlos Linares López19315.67