Authors: Pham Dang Hai
Random Boolean networks, a generalization of cellular automata, were originally introduced as a simple model of genetic regulatory networks, but they are also used as mathematical models for studying complex dynamical systems with a large number of coupled variables. Simulating sequentially large networks with high connectivity meets often with difficulties on the time and the memory. We propose here a multi-agent based approach for simulating large random Boolean networks, which promises to give an improvement of its performance by using multiprocessors systems.