AI RESEARCH
Benefits of Low-Cost Bio-Inspiration in the Age of Overparametrization
arXiv CS.AI
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ArXi:2604.20365v1 Announce Type: cross While Central Pattern Generators (CPGs) and Multi-Layer Perceptrons (MLP) are widely used paradigms in robot control, few systematic studies have been performed on the relative merits of large parameter spaces. In contexts where input and output spaces are small and performance is bounded, having parameters to optimize may actively hinder the learning process instead of empowering it.