• DocumentCode
    2915452
  • Title

    Fitness functions for the unconstrained evolution of digital circuits

  • Author

    Kuyucu, Tüze ; Trefzer, Martin ; Greensted, Andrew ; Miller, Julian ; Tyrrell, A.

  • Author_Institution
    Intell. Syst. Group, York Univ., York
  • fYear
    2008
  • fDate
    1-6 June 2008
  • Firstpage
    2584
  • Lastpage
    2591
  • Abstract
    This work is part of a project that aims to develop and operate integrated evolvable hardware systems using unconstrained evolution. Experiments are carried out on an evolvable hardware platform featuring both combinatorial and registered logic as well as sequential feedback loops. In order to be able to accurately assess the transient output of the system and at the same time speed up evolution, new fitness evaluation methods are introduced. These bitwise and hierarchical fitness evaluation methods are adapted and further developed specifically for hardware implementation. It is shown that the newly developed approaches are particularly powerful in coping with two important issues: computational ambiguities, which generally occur when evaluating binary strings, and transient effects resulting from measuring hardware output. On two combinatorial problems it is shown that the new fitness functions improve the performance of evolution and allow stable solutions to be found more reliably. The experiments are carried out with a recently developed hardware platform called reconfigurable integrated system array (RISA).
  • Keywords
    combinational circuits; combinatorial mathematics; digital circuits; evolutionary computation; binary strings; combinatorial logic; combinatorial problems; digital circuits unconstrained evolution; fitness functions; hierarchical fitness evaluation methods; integrated evolvable hardware systems; reconfigurable integrated system array; registered logic; sequential feedback loops; Concurrent computing; Digital circuits; Evolutionary computation; Feedback loop; Genetic programming; Hardware; Logic; Particle measurements; Power system reliability; Sampling methods;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Evolutionary Computation, 2008. CEC 2008. (IEEE World Congress on Computational Intelligence). IEEE Congress on
  • Conference_Location
    Hong Kong
  • Print_ISBN
    978-1-4244-1822-0
  • Electronic_ISBN
    978-1-4244-1823-7
  • Type

    conf

  • DOI
    10.1109/CEC.2008.4631145
  • Filename
    4631145