TY - GEN
T1 - Influences of Artificial Speciation on Morphological Robot Evolution
AU - Carlo, Matteo De
AU - Zeeuwe, Daan
AU - Ferrante, Eliseo
AU - Meynen, Gerben
AU - Ellers, Jacintha
AU - Eiben, A. E.
N1 - Publisher Copyright:
© 2020 IEEE.
PY - 2020/12/1
Y1 - 2020/12/1
N2 - One key challenge in Evolutionary Robotics (ER) is to evolve morphology and controllers of robots. Most experiments in the field converge rapidly to a single solution for the entire population. Early convergence results in a premature loss of diversity, which creates inconsistent results across multiple runs, sometimes converging to a local optimum. In Nature we can observe the opposite behavior: the more time passes, the more life becomes increasingly diverse. The increasing diversity is correlated to the formation of new species, which is catalyzed by reproductive isolation caused by physical or behavioral separation. Inspired by natural evolution, in this paper we apply artificial speciation based on morphological traits to an ER system. Individuals are forced to crossover only with individuals within the same species and a protection mechanism is applied to newly created species. In our experiments, we demonstrate that this speciation mechanism, inspired by NEAT, can evolve a population rich of many coexisting individuals, differing both in morphology and behavior.
AB - One key challenge in Evolutionary Robotics (ER) is to evolve morphology and controllers of robots. Most experiments in the field converge rapidly to a single solution for the entire population. Early convergence results in a premature loss of diversity, which creates inconsistent results across multiple runs, sometimes converging to a local optimum. In Nature we can observe the opposite behavior: the more time passes, the more life becomes increasingly diverse. The increasing diversity is correlated to the formation of new species, which is catalyzed by reproductive isolation caused by physical or behavioral separation. Inspired by natural evolution, in this paper we apply artificial speciation based on morphological traits to an ER system. Individuals are forced to crossover only with individuals within the same species and a protection mechanism is applied to newly created species. In our experiments, we demonstrate that this speciation mechanism, inspired by NEAT, can evolve a population rich of many coexisting individuals, differing both in morphology and behavior.
KW - evolutionary computing
KW - evolutionary robotics
KW - robotics
KW - species
UR - http://www.scopus.com/inward/record.url?scp=85099707749&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85099707749&partnerID=8YFLogxK
U2 - 10.1109/SSCI47803.2020.9308433
DO - 10.1109/SSCI47803.2020.9308433
M3 - Conference contribution
AN - SCOPUS:85099707749
T3 - 2020 IEEE Symposium Series on Computational Intelligence, SSCI 2020
SP - 2272
EP - 2279
BT - 2020 IEEE Symposium Series on Computational Intelligence, SSCI 2020
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2020 IEEE Symposium Series on Computational Intelligence, SSCI 2020
Y2 - 1 December 2020 through 4 December 2020
ER -