Models of massive parallelism: analysis of cellular automata and neural networks
Models of massive parallelism: analysis of cellular automata and neural networks
Small worlds: the dynamics of networks between order and randomness
Small worlds: the dynamics of networks between order and randomness
Perturbing the Regular Topology of Cellular Automata: Implications for the Dynamics
ACRI '01 Proceedings of the 5th International Conference on Cellular Automata for Research and Industry
Statistical mechanics of complex networks
Statistical mechanics of complex networks
ACRI'06 Proceedings of the 7th international conference on Cellular Automata for Research and Industry
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We investigate the performances and collective task-solving capabilities of complex networks of automata using the density problem as a typical case We show by computer simulations that evolved Watts–Strogatz small-world networks have superior performance with respect to scale-free graphs of the Albert–Barabási type Besides, Watts–Strogatz networks are much more robust in the face of transient uniformly random perturbations This result differs from information diffusion on scale-free networks, where random faults are highly tolerated.