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Evolving-Controllers Versus Learning-Controllers for Morphologically Evolvable Robots
- Source :
- Vrije Universiteit Amsterdam Repository
- Publication Year :
- 2020
-
Abstract
- We investigate an evolutionary robot system where (simulated) modular robots can reproduce and create robot children that inherit the parents’ morphologies by crossover and mutation. Within this system we compare two approaches to creating good controllers, i.e., evolution only and evolution plus learning. In the first one the controller of a robot child is inherited, so that it is produced by applying crossover and mutation to the controllers of its parents. In the second one the controller of the child is also inherited, but additionally, it is enhanced by a learning method. The experiments show that the learning approach does not only lead to different fitness levels, but also to different (bigger) robots. This constitutes a quantitative demonstration that changes in brains, i.e., controllers, can induce changes in the bodies, i.e., morphologies.
Details
- Database :
- OAIster
- Journal :
- Vrije Universiteit Amsterdam Repository
- Notes :
- Castillo, Pedro A., Jiménez Laredo, Juan Luis, Fernández de Vega, Francisco (Ed.), Applications of Evolutionary Computation: 23rd European Conference, EvoApplications 2020, Held as Part of EvoStar 2020, Seville, Spain, April 15–17, 2020, Proceedings, p.86-99. Springer. [ISBN 9783030437213], English
- Publication Type :
- Electronic Resource
- Accession number :
- edsoai.on1362437126
- Document Type :
- Electronic Resource
- Full Text :
- https://doi.org/10.1007.978-3-030-43722-0_6