Multiobjective techniques for the use of state in genetic programming applied to simulated car racing

Alexandras Agapitos, Julian Togelius, Simon M. Lucas

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Abstract

    Multi-objective optimisation is applied to encourage the effective use of state variables in car controlling programs evolved using Genetic Programming. Three different metrics for measuring the use of state within a program are introduced. Comparisons are performed among multi- and single-objective fitness functions with respect to learning speed and final fitness of evolved individuals, and attempts are made at understanding whether there is a trade-off between good performance and stateful controllers in this problem domain.

    Original languageEnglish (US)
    Title of host publication2007 IEEE Congress on Evolutionary Computation, CEC 2007
    Pages1562-1569
    Number of pages8
    DOIs
    StatePublished - 2007
    Event2007 IEEE Congress on Evolutionary Computation, CEC 2007 - , Singapore
    Duration: Sep 25 2007Sep 28 2007

    Other

    Other2007 IEEE Congress on Evolutionary Computation, CEC 2007
    CountrySingapore
    Period9/25/079/28/07

    Fingerprint

    Genetic programming
    Multiobjective optimization
    Genetic Programming
    Railroad cars
    Controllers
    Fitness Function
    Multi-objective Optimization
    Fitness
    Objective function
    Trade-offs
    Controller
    Metric
    Learning

    ASJC Scopus subject areas

    • Artificial Intelligence
    • Software
    • Theoretical Computer Science

    Cite this

    Agapitos, A., Togelius, J., & Lucas, S. M. (2007). Multiobjective techniques for the use of state in genetic programming applied to simulated car racing. In 2007 IEEE Congress on Evolutionary Computation, CEC 2007 (pp. 1562-1569). [4424659] https://doi.org/10.1109/CEC.2007.4424659

    Multiobjective techniques for the use of state in genetic programming applied to simulated car racing. / Agapitos, Alexandras; Togelius, Julian; Lucas, Simon M.

    2007 IEEE Congress on Evolutionary Computation, CEC 2007. 2007. p. 1562-1569 4424659.

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Agapitos, A, Togelius, J & Lucas, SM 2007, Multiobjective techniques for the use of state in genetic programming applied to simulated car racing. in 2007 IEEE Congress on Evolutionary Computation, CEC 2007., 4424659, pp. 1562-1569, 2007 IEEE Congress on Evolutionary Computation, CEC 2007, Singapore, 9/25/07. https://doi.org/10.1109/CEC.2007.4424659
    Agapitos A, Togelius J, Lucas SM. Multiobjective techniques for the use of state in genetic programming applied to simulated car racing. In 2007 IEEE Congress on Evolutionary Computation, CEC 2007. 2007. p. 1562-1569. 4424659 https://doi.org/10.1109/CEC.2007.4424659
    Agapitos, Alexandras ; Togelius, Julian ; Lucas, Simon M. / Multiobjective techniques for the use of state in genetic programming applied to simulated car racing. 2007 IEEE Congress on Evolutionary Computation, CEC 2007. 2007. pp. 1562-1569
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