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