Embodied Evolution: Embodying an Evolutionary Algorithm in a Population of Robots (1999)
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| Venue: | CONGRESS ON EVOLUTIONARY COMPUTATION |
| Citations: | 43 - 7 self |
BibTeX
@INPROCEEDINGS{Watson99embodiedevolution:,
author = {Richard A. Watson and Sevan G. Ficici and Jordan B. Pollack},
title = {Embodied Evolution: Embodying an Evolutionary Algorithm in a Population of Robots},
booktitle = {CONGRESS ON EVOLUTIONARY COMPUTATION},
year = {1999},
pages = {335--342},
publisher = {IEEE Press}
}
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Abstract
... methodology for the automatic design of robotic controllers. EE is an evolutionary robotics (ER) technique that avoids the pitfalls of the simulate-and-transfer method, allows the speed-up of evaluation time by utilizing parallelism, and is particularly suited to future work on multi-agent behaviors. In EE, an evolutionary algorithm is distributed amongst and embodied within a population of physical robots that reproduce with one another while situated in the task environment. We have built a population of eight robots and successfully implemented our first experiments. The controllers evolved by EE compare favorably to hand-designed solutions for a simple task. We detail our methodology, report our initial results, and discuss the application of EE to more advanced and distributed robotics tasks.
