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EP137 Ken Stanley on Neuroevolution

The Jim Rutt Show

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Evolving Neural Networks: Insights from Nature

This chapter explores the concept of indirect encoding and its parallels with biological evolution, particularly highlighting how limited genetic codes can lead to complex neural structures. It discusses Compositional Pattern-Producing Networks (CPPNs) and their role in evolving effective neural networks, while emphasizing the efficiency of computational models compared to natural processes. The speakers also examine the implications of evolutionary development on neuroevolution, questioning the necessity of certain biological constraints in the context of artificial intelligence.

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