ALTALT: Combining graphplan and heuristic state search

B. Srivastava, X. Nguyen, Subbarao Kambhampati, M. B. Do, U. Nambiar, Z. Nie, R. Nigenda, T. Zimmerman

Research output: Contribution to journalArticlepeer-review

5 Scopus citations

Abstract

We briefly describe the implementation and evaluation of a novel plan synthesis system, called ALTALT. ALTALT is designed to exploit the complementary strengths of two of the currently popular competing approaches for plan generation: (1) GRAPHPLAN and (2) heuristic state search. It uses the planning graph to derive effective heuristics that are then used to guide heuristic state search. The heuristics derived from the planning graph do a better job of taking the subgoal interactions into account and, as such, are significantly more effective than existing heuristics. ALTALT was implemented on top of two state-of-the-art planning systems: (1) STAN3.0, a GRAPHPLAN-style planner, and (2) HSP-R, a heuristic search planner.

Original languageEnglish (US)
Pages (from-to)88-90
Number of pages3
JournalAI Magazine
Volume22
Issue number3
StatePublished - Sep 1 2001

ASJC Scopus subject areas

  • Artificial Intelligence

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