Learning by probabilistic Boolean networks

Boolean networks, in spite of their structural simplicity, seem to be able to simulate the dynamics of complex biological and nonbiological systems. Learning algorithms in neural networks have shown to be a very promising approach to some problems connected to artificial intelligence. Positive feedback has been successfully used by the genetic algorithm and the ant system. In this paper we propose an adaptive Boolean network that takes advantage of all these properties.<
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