Proceedings of the seventh international conference (1990) on Machine learning
Genetic programming: on the programming of computers by means of natural selection
Genetic programming: on the programming of computers by means of natural selection
Evolving multiple agents by genetic programming
Advances in genetic programming
Improving performance of GP by adaptive terminal selection
PRICAI'00 Proceedings of the 6th Pacific Rim international conference on Artificial intelligence
A nervous system model for direct dynamics animation control based on evolutionary computation
Proceedings of the 2008 ACM symposium on Applied computing
Dynamic population variation in genetic programming
Information Sciences: an International Journal
Abandoning objectives: Evolution through the search for novelty alone
Evolutionary Computation
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This paper shows how the computational model, which simulates the coordinated movements of human-like bipedal locomotion, can be evolutionally generated without the elaboration of manual coding. In the research on bio-mechanical engineering, robotics and neurophysiology, the mechanism of human bipedal walking is of major interest. It can serve as a basis for developing several applications such as computer animation and humanoid robots. Nevertheless, because of the complexity of human's neuronal system that interacts with the body dynamics making the walking movements, much is left unknown about the control mechanism of locomotion, and researchers were looking for the optimal model of the neuronal system by extensive efforts of trial and error. In this work, genetic programming is utilized to induce the model of the neural system automatically and its effectives are shown by simulating a human bipedal gait with the obtained model. The experimental results show some promising evidence for evolutionary generation of the human-like bipedal locomotion.