Heuristic search in networks with modifiable estimate

  • Authors:

  • A. Mahanti;K. Ray

  • Affiliations:

  • Indian Institute of Management Calcutta, Post Box 16757, Calcutta 700 027, India;Regional Computer Centre Calcutta, Jadavpur University Campus, Calcutta 700 032, India

  • Venue:
  • CSC '87 Proceedings of the 15th annual conference on Computer Science
  • Year:
  • 1987

Quantified Score

Hi-index 0.01

Visualization

Abstract

In a recent study, L. Mero suggested a method for run-time modification of heuristic estimate of nodes. An algorithm, called B′, was presented. Performance of B′ was analysed under modifiable and admissible heuristics. It was claimed that B′ was an improved version of a polynomial time bound algorithm, namely B, originally due to Martelli. While in turn B was based on the Algorithm A introduced by Hart, Nilsson et al.Surprisingly, it is observed that B′ can make exponential number of node expansions in the worst case. In particular B′ can make more node expansions than B and also than A! If heuristic is not admissible B′ can output worse solution that B (or A). Under the same framework of modifiable heuristics a new algorithm, called D, is proposed. It is shown that D makes polynomial number of node expansions in the worst case and always finds a solution which is at least as good as that found by B′ and B. Algorithm D is compared with Algorithm C presented by Bagchi and Mahanti. Algorithm C, in general, showed better performance than other algorithms. Here it is shown that C and D output same solution but D makes less number of node expansions than C. The admissibility condition is relaxed and results are proved under a general assumption that heuristic estimate is only non-negative.