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Agent motion planning with GAs enhanced by memory models.

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


Martijn Bot

Ken Chisholm


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


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


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