Network Search Algorithms with Modifiable Heuristics

Abstract

Most of the previous studies in heuristic search have assumed that the heuristic estimate of a node remains constant during the execution of algorithms In a recent study, L. Mero suggested a method for run-time modification of heuristic estimate of nodes. This method of modifiable heuristics can in general reduce the total number of node expansions. It is shown in this paper, with counter examples, that Mero’s algorithm (B′) is not as good as claimed.

Under the same framework of modifiable heuristics a new algorithm, called D, is developed. Algorithm D is a modified version of Algorithm C, originally due to Bagchi and Mahanti. This new algorithm is strictly better than C, as D expands no more nodes than C and yet gives the solution of the same cost. Importance of D follows from the fact that C has the following nice properties: (i) C finds at least as good or better solution than found by A (due to Hart, Nilsson et al) or B (due to Martelli); and (ii) B and C are both O(N ²) algorithms. As in case of C, here also the admissibility condition is relaxed and results are proved under a general assumption that heuristic estimate is only non-negative.