Evolving-Controllers Versus Learning-Controllers for Morphologically Evolvable Robots
| Autor: | Miras, Karine, De Carlo, Matteo, Akhatou, Sayfeddine, Eiben, A. E., Castillo, Pedro A., Jiménez Laredo, Juan Luis, Fernández de Vega, Francisco |
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| Přispěvatelé: | Artificial intelligence, Network Institute, Artificial Intelligence (section level), Computational Intelligence, Knowledge Representation and Reasoning, Castillo, Pedro A., Jiménez Laredo, Juan Luis, Fernández de Vega, Francisco |
| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: |
Self-reconfiguring modular robot
Modular robots Computer science Crossover Evolutionary robotics 02 engineering and technology 03 medical and health sciences 0302 clinical medicine Control theory 0202 electrical engineering electronic engineering information engineering Morphological evolution business.industry technology industry and agriculture body regions Life-time learning Robotic systems Mutation (genetic algorithm) Robot Learning methods 020201 artificial intelligence & image processing Artificial intelligence Evolutionary Robotics business human activities 030217 neurology & neurosurgery |
| Zdroj: | Applications of Evolutionary Computation: 23rd European Conference, EvoApplications 2020, Held as Part of EvoStar 2020, Seville, Spain, April 15–17, 2020, Proceedings, 86-99 STARTPAGE=86;ENDPAGE=99;TITLE=Applications of Evolutionary Computation Applications of Evolutionary Computation ISBN: 9783030437213 EvoApplications Miras, K, De Carlo, M, Akhatou, S & Eiben, A E 2020, Evolving-Controllers Versus Learning-Controllers for Morphologically Evolvable Robots . in P A Castillo, J L Jiménez Laredo & F Fernández de Vega (eds), Applications of Evolutionary Computation : 23rd European Conference, EvoApplications 2020, Held as Part of EvoStar 2020, Seville, Spain, April 15–17, 2020, Proceedings . Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 12104 LNCS, Springer, pp. 86-99, 23rd European Conference on Applications of Evolutionary Computation, EvoApplications 2020, held as part of EvoStar 2020, Seville, Spain, 15/04/20 . https://doi.org/10.1007/978-3-030-43722-0_6 |
| DOI: | 10.1007/978-3-030-43722-0_6 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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