Agent motion planning with GAs enhanced by memory models.

Bot, Martijn; Urquhart, Neil B; Chisholm, Ken

Abstract

The Tartarus problem may be considered a benchmark problem in the field of robotics. A robotic agent is required to move a number of blocks to the edge of an environment. The location of the blocks and position of the robot is unknown initially. The authors present a framework that allows the agent to learn about its environment and plan ahead using a GA to solve the problem. The authors prove that the GA based method provides the best published result on the Tartarus problem. An exhaustive search is used within the framework as a comparison, this provides a higher score still. This paper presents the two best Tartarus results yet published

Citation

Bot, M., Urquhart, N. B., & Chisholm, K. (2001). Agent motion planning with GAs enhanced by memory models. Genetic and Evolutionary Computation Conference, 227-234

• Journal Article Type: Article
• Publication Date: 2001
• Deposit Date: Jun 30, 2010
• Publicly Available Date: Jun 30, 2010
• Peer Reviewed: Peer Reviewed
• Pages: 227-234
• ISBN: 1-55860-774-9
• Keywords: Tartarus; robotic agent; GA; memory models
• Public URL: http://researchrepository.napier.ac.uk/id/eprint/3300