Elsevier

Fuzzy Sets and Systems

Volume 82, Issue 3, 23 September 1996, Pages 351-355
Fuzzy Sets and Systems

Iterative-deepening fuzzy heuristic search algorithms and their learning investigation

https://doi.org/10.1016/0165-0114(95)00226-XGet rights and content

Abstract

This paper presents a fuzzy, heuristic search algorithm FIDA∗ that applies iterative-deepening methods and dynamic modification of the heuristic function. It then improves the FIDA∗ algorithm by incorporating methods to propagate the modified heuristic function, 9t(n). It is pointed out that the algorithm FIDA∗ can be applied to learn over repeated uses on problems with the same state space and goal node. This paper presents a learning algorithm, LFIDA∗ can be applied to learn over repeated uses on difficulties that often occur in designing 9t(n).

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