Performance of IDA on trees and graphs

  • Authors:

  • Ambuj Mahanti;Subrata Ghosh;Dana S. Nau;Asim K. Pal;Laveen Kanall

  • Affiliations:

  • Systems Res. Ctr., U. of Maryland, College Park, MD and Computer Science Department;Comp. Sci. Dept., U. of Maryland, College Park, MD;Comp. Sci. Dept., U. of Maryland, College Park, MD and Systems Research Center and the Institute for Advanced Computer Studies;IIM, Calcutta, Calcutta, India;Comp. Sci. Dept., U. of Maryland, College Park, MD

  • Venue:
  • AAAI'92 Proceedings of the tenth national conference on Artificial intelligence
  • Year:
  • 1992

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Abstract

We present the following results about IDA * and related algorithms: • We show that IDA * is not asymptotically optimal in all of the cases where it was thought to be so. In particular, there are trees satisfying all of the conditions previously thought to guarantee asymptotic optimality for IDA *, such that IDA * will expand more than O(N) nodes, where N is the number of nodes eligible for expansion by A*. • We present a new set of necessary and sufficient conditions to guarantee that IDA * expands O(N) nodes on trees. • On trees not satisfying the above conditions, there is no best-first admissible tree search algorithm that runs in S = N/Ψ(N) (where Ψ(N) ≠ O(1)) memory and always expands O(N) nodes. • There are acyclic graphs on which IDA * expands Ω(22N) nodes.