Abstract
A neural network model is presented which is an abstraction of many real world adaptable control systems that seems to be sufficiently complex to provide interesting results, yet simple enough that computer simulations of its evolution can be carried out in weeks rather than years. Some preliminary explorations of the interaction between learning and evolution in this system are described, together with some suggestions for future research in this area.
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References
Baldwin, J.M. (1896). A New Factor in Evolution. The American Naturalist, 30, 441–451.
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© 2001 Springer-Verlag London
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Bullinaria, J.A. (2001). Exploring the Baldwin Effect in Evolving Adaptable Control Systems. In: French, R.M., Sougné, J.P. (eds) Connectionist Models of Learning, Development and Evolution. Perspectives in Neural Computing. Springer, London. https://doi.org/10.1007/978-1-4471-0281-6_23
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DOI: https://doi.org/10.1007/978-1-4471-0281-6_23
Publisher Name: Springer, London
Print ISBN: 978-1-85233-354-6
Online ISBN: 978-1-4471-0281-6
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