Incremental acquisition of neural structures through evolution

Zusammenfassung (Abstract) :

In this contribution we present a novel method, called Evolutionary Acquisition of Neural Topologies (EANT), for evolving the structures and weights of neural networks. The method uses an efficient and compact genetic encoding of a neural network into a linear genome that enables a network’s outputs to be computed without the network being decoded. Furthermore, it uses a nature inspired metalevel evolutionary process where new structures are explored at a larger timescale, and existing structures are exploited at a smaller timescale. Because of this, the method is able to find minimal neural structures for solving a given learning task.

Stichworte :

neural networks, reinforcement learning, evolutionary methods