Abstract
Embodied evolution is an evolutionary robotics approach that implements an evolutionary algorithm over a population of robots and evolves while the robots perform their tasks. So far, most studies on embodied evolution utilize relatively simple neural networks as robot controllers. However, a simple structured controller might restrict robot behavior and lead to lower performance. This paper proposes an embodied evolution approach that uses echo state networks as robot controllers. The experiments are conducted using computer simulations, and the controllers are evolved in a two-target navigation task. The results show that the echo state network controllers outperform the conventional controllers.
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This work was partially supported by JSPS KAKENHI Grant Number JP21J14922.
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Hiraga, M., Katada, Y. & Ohkura, K. Echo state networks for embodied evolution in robotic swarms. Artif Life Robotics 28, 139–147 (2023). https://doi.org/10.1007/s10015-022-00828-w
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DOI: https://doi.org/10.1007/s10015-022-00828-w