Developmental Plasticity in Cartesian Genetic Programming Artificial Neural Networks
نویسندگان
چکیده
This work presents a method for exploiting developmental plasticity in Artificial Neural Networks using Cartesian Genetic Programming. This is inspired by developmental plasticity that exists in the biological brain allowing it to adapt to a changing environment. The network architecture used is that of a static Cartesian Genetic Programming ANN, which has recently been introduced. The network is plastic in terms of its dynamic architecture, connectivity, weights and functionality that can change in response to the environmental signals. The dynamic capabilities of the algorithm are tested on a standard benchmark linear/non-linear control problems (i.e. pole-balancing).
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تاریخ انتشار 2012