INSPIRING FUTURES

Agent motion planning with GAs enhanced by memory models.

Bot, Martijn, Urquhart, Neil B and Chisholm, Ken (2001) Agent motion planning with GAs enhanced by memory models. Genetic and Evolutionary Computation Conference - GECCO 2001. pp. 227-234.

[img]
Preview
PDF
Available under License Creative Commons Attribution Non-commercial.

Download (136kB) | Preview

    Abstract/Description

    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

    Item Type: Article
    ISBN: 1-55860-774-9
    Uncontrolled Keywords: Tartarus; robotic agent; GA; memory models;
    University Divisions/Research Centres: Faculty of Engineering, Computing and Creative Industries > School of Computing
    Dewey Decimal Subjects: 600 Technology > 620 Engineering > 629 Vehicle engineering
    Library of Congress Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering
    Item ID: 3300
    Depositing User: Computing Research
    Date Deposited: 30 Jun 2010 13:17
    Last Modified: 12 Sep 2013 11:40
    URI: http://researchrepository.napier.ac.uk/id/eprint/3300

    Actions (login required)

    View Item

    Document Downloads

    More statistics for this item...

    Edinburgh Napier University is a registered Scottish charity. Registration number SC018373