Marcin Suchorzewski

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In this paper we introduce the Developmental Symbolic Encoding (DSE), a new generative encoding for evolving networks (e.g. neural or boolean). DSE combines elements of two powerful generative encodings, Cellular Encoding and HyperNEAT, in order to evolve networks that are modular, regular, scale-free, and scalable. Generating networks with these properties(More)
Evolutionary neural networks, or neuroevolution, appear to be a promising way to build versatile adaptive systems, combining evolution and learning. One of the most challenging problems of neuroevolution is finding a scalable and robust genetic representation, which would allow to effectively grow increasingly complex networks for increasingly complex(More)
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