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Evolving stable behavior in a spino-neuromuscular system model

Authors:

Stan Gotshall,

Terry SouleAuthors Info & Claims

GECCO '08: Proceedings of the 10th annual conference on Genetic and evolutionary computation

Pages 283 - 284

https://doi.org/10.1145/1389095.1389140

Published: 12 July 2008 Publication History

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Abstract

This paper demonstrates the effectiveness of genetic algorithms in training stable behavior in a model of the spino-neuromuscular system (SNMS). In particular, we test the stability of trained instances of the model with respect to unfamiliar control signals and untrained forearm weights. The results show that small changes to the input frequency and forearm weight result in small changes in velocity, demonstrating that the system can reasonably accommodate unfamiliar circumstances. This type of stability is a critical feature for virtually any type of control system.

References

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A. P. Georgopoulos, J. T. Lurito, M. Petrides, A. B. Schwartz, and J. T. Massey. Mental Rotation of the Neuronal Population Vector. Science, 243:234--236, 1989.

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[3]

S. Gotshall, K. Browder, J. Sampson, T. Soule, and R. Wells. Stochastic Optimization of a Biologically Plausible Spino-neuromuscular System Model: A Comparison with Human Subjects. Genetic Programming and Evolvable Machines, 8(4)355--380, 2007.

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R.E. Kettner, A.B. Schwartz, and A.P. Georgopoulos. Positional Gradients and Population Coding of Movement Direction from Various Movement Origins. Journal of Neuroscience, 8:2938--2947, 1988.

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Index Terms

Evolving stable behavior in a spino-neuromuscular system model
1. Computing methodologies
  1. Artificial intelligence
    1. Philosophical/theoretical foundations of artificial intelligence

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GECCO '08: Proceedings of the 10th annual conference on Genetic and evolutionary computation

July 2008

1814 pages

ISBN:9781605581309

DOI:10.1145/1389095

Conference Chair:
Conor Ryan
University of Limerick, Ireland
,
Editor:
Maarten Keijzer
Chordiant Software International B.V., The Netherlands

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 12 July 2008

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GECCO08: Genetic and Evolutionary Computation Conference

July 12 - 16, 2008

GA, Atlanta, USA

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Overall Acceptance Rate 1,669 of 4,410 submissions, 38%

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Index Terms

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Stochastic training of a biologically plausible spino-neuromuscular system model

Stability and Stabilization Criteria for a Class of Uncertain Neutral Systems with Time-Varying Delays

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