Fitness functions in evolutionary robotics: A survey and analysis
Robotics and Autonomous Systems
IWANN'07 Proceedings of the 9th international work conference on Artificial neural networks
Emergent generality of adapted locomotion gaits of simulated snake-like robot
EuroGP'06 Proceedings of the 9th European conference on Genetic Programming
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We propose a novel perspective on the use of evolutionary multiobjective optimization (EMO) as a paradigm for evolving embodied organisms and as a framework for characterizing complexity. The paper demonstrates novel experiments that show the power of EMO in generating robots with different morphologies, yet with very similar locomotion abilities. The proposed framework for comparing the complexity of an object across different complexity measures allowed meaningful and quantifiable comparisons between the evolved organisms. We show empirically that the partial order feature inherited in the Pareto concept exhibits characteristics which are suitable for comparing between the complexities of artificially evolved embodied organisms.