DocumentCode :
2983232
Title :
Evolvability in Evolutionary Robotics: Evolving the Genotype-Phenotype Mapping
Author :
Koenig, Lionel ; Schmeck, Hartmut
Author_Institution :
Inst. AIFB, Karlsruhe Inst. of Technol., Karlsruhe, Germany
fYear :
2010
fDate :
Sept. 27 2010-Oct. 1 2010
Firstpage :
259
Lastpage :
260
Abstract :
A completely evolvable genotype-phenotype mapping (ceGPM) is studied with respect to its capability of improving the flexibility of artificial evolution. By letting mutation affect not only controller genotypes, but also the mapping from genotype to phenotype, the future e effects of mutation can change over time. In this way, the need for prior parameter adaptation can be reduced. Experiments indicate that the ceGPM is capable of robustly adapting to a benchmark behavior. A comparison to a related approach shows significant improvements in evolvability.
Keywords :
artificial life; evolutionary computation; multi-robot systems; self-adjusting systems; artificial evolution; evolutionary robotics; genotype-phenotype mapping; mutation affect; parameter adaptation; Aerospace electronics; Automata; Bars; Mobile robots; Robot sensing systems;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Self-Adaptive and Self-Organizing Systems (SASO), 2010 4th IEEE International Conference on
Conference_Location :
Budapest
Print_ISBN :
978-1-4244-8537-6
Electronic_ISBN :
978-0-7695-4232-4
Type :
conf
DOI :
10.1109/SASO.2010.27
Filename :
5630047
Link To Document :
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