Computer Science – Artificial Intelligence
Scientific paper
1998-10-16
"Recent Advances in AI Planning" (Sam Steel & Rachid Alami eds.), p. 312-325, Springer 1997 (LNAI 1348)
Computer Science
Artificial Intelligence
13 pages, European Conference on Planning 1997
Scientific paper
In this paper we describe SYNERGY, which is a highly parallelizable, linear planning system that is based on the genetic programming paradigm. Rather than reasoning about the world it is planning for, SYNERGY uses artificial selection, recombination and fitness measure to generate linear plans that solve conjunctive goals. We ran SYNERGY on several domains (e.g., the briefcase problem and a few variants of the robot navigation problem), and the experimental results show that our planner is capable of handling problem instances that are one to two orders of magnitude larger than the ones solved by UCPOP. In order to facilitate the search reduction and to enhance the expressive power of SYNERGY, we also propose two major extensions to our planning system: a formalism for using hierarchical planning operators, and a framework for planning in dynamic environments.
No associations
LandOfFree
SYNERGY: A Linear Planner Based on Genetic Programming does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.
If you have personal experience with SYNERGY: A Linear Planner Based on Genetic Programming, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and SYNERGY: A Linear Planner Based on Genetic Programming will most certainly appreciate the feedback.
Profile ID: LFWR-SCP-O-587392