Genetic programming: on the programming of computers by means of natural selection
Genetic programming: on the programming of computers by means of natural selection
Explorations in evolutionary robotics
Adaptive Behavior
An introduction to differential evolution
New ideas in optimization
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Evolutionary Robotics: The Biology,Intelligence,and Technology
Evolutionary Robotics: The Biology,Intelligence,and Technology
Journal of Global Optimization
Differential Evolution: In Search of Solutions (Springer Optimization and Its Applications)
Differential Evolution: In Search of Solutions (Springer Optimization and Its Applications)
Differential evolution in constrained numerical optimization: An empirical study
Information Sciences: an International Journal
Evolution and analysis of a robot controller based on a gene regulatory network
ICES'10 Proceedings of the 9th international conference on Evolvable systems: from biology to hardware
The evolution of signal communication for the e-puck robot
MICAI'11 Proceedings of the 10th Mexican international conference on Advances in Artificial Intelligence - Volume Part I
Evolution of homing navigation in a real mobile robot
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Minimal representation multisensor fusion using differential evolution
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
IEEE Transactions on Neural Networks
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In Evolutionary Robotics, Bioinspired Algorithms are used to generate robotic behavior. Several researchers used classic Genetic Algorithms or adaptations of Genetic Algorithms for developing experiments in ER. Here, we use Differential Evolution as an evolutionary alternative method to automatically obtain robotic behaviors, selecting a wall-following behavior as a representative example. We used an e-puck robot and the Player-Stage simulator for the experiments. We detail the results and the advantages when using the DE variants in our application with the simulated and the real robot. In order to optimize time for evolution, and test the resultant behavior in the e-puck robot, for our experiments we employed the Player-Stage simulator.