Ronen I. Brafman
Department of Math and Computer Science
Ben-Gurion University
Beer Sheva, ISRAEL 84105
email: brafman@cs.bgu.ac.il
Holger H. Hoos
Department of Computer Science
Darmstadt University of Technology
D-62483 Darmstadt, GERMANY
email: hoos@informatik.tu-darmstadt.de
Craig Boutilier
Department of Computer Science
University of British Columbia
Vancouver, BC, CANADA, V6T 1Z4
email: cebly@cs.ubc.ca
Abstract
We describe LPSP, a domain-independent planning algorithm that
searches the space of linear plans using stochastic local search
techniques. Because linear plans, rather than propositional
assignments, comprise the states of LPSP's search space, we can
incorporate into its search various operators that are suitable for
manipulating plans, such as plan-step reordering based on action
dependencies, and limited forward/backward search. This, in turn,
leads to a flexible planning algorithm that outperforms
the SATPLAN planner on difficult blocks world problems.
Submitted, 1998
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