Artificial Evolution of Plastic Neural Networks: a few Key Concepts

Abstract : This paper introduces a hierarchy of concepts to classify the goals and the methods of works that mix neuro-evolution and synaptic plasticity. We propose definitions of “behavioral robustness” and oppose it to “reward-based behavioral changes”; we then distinguish the switch between behaviors and the acquisition of new behaviors. Last, we formalize the concept of “synaptic General Learning Abilities” (sGLA) and that of “synaptic Transitive Learning Abilities (sTLA)”. For each concept, we review the literature to identify the main experimental setups and the typical studies.
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Jean-Baptiste Mouret, Paul Tonelli. Artificial Evolution of Plastic Neural Networks: a few Key Concepts. Taras Kowaliw, Nicolas Bredeche, René Doursat. Growing Adaptive Machines: combining Development and Learning in Artificial Neural Networks, 557, Springer, pp.251-261, 2014, 978-3-642-55336-3. ⟨http://www.springer.com/us/book/9783642553363⟩. ⟨hal-01300702⟩

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