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
Link To Document :
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