Research Output
Agent motion planning with GAs enhanced by memory models.
  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

  • Type:


  • Publication Status:


  • Library of Congress:

    TK Electrical engineering. Electronics Nuclear engineering

  • Dewey Decimal Classification:

    629 Vehicle engineering


Bot, M., Urquhart, N. B. & Chisholm, K. (2000). Agent motion planning with GAs enhanced by memory models. Genetic and Evolutionary Computation Conference. , 227-234



Tartarus; robotic agent; GA; memory models;

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