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ALTALT Combining Graphplan and Heuristic State Search

Authors :
Srivastava, Biplav
Nguyen, XuanLong
Kambhampati, Subbarao
Do, Minh B.
Nambiar, Ullas
Nie, Zaiqing
Nigenda, Romeo
Zimmerman, Terry
Source :
AI Magazine. Fall, 2001, Vol. 22 Issue 3, p88
Publication Year :
2001

Abstract

ALTALT(1) combines the complementary strengths of two of the currently popular competing approaches for plan generation: (1) GRAPHPLAN and (2) heuristic state search. The planner has evolved from the initial […]<br />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.

Details

ISSN :
07384602
Volume :
22
Issue :
3
Database :
Gale General OneFile
Journal :
AI Magazine
Publication Type :
Periodical
Accession number :
edsgcl.79573620