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We present discrete stochastic mathematical models for the growth curves of synchronous and synchronous evolutionary algorithms with populations structured ccording to a random graph. We show that, to good approximation, randomly structured and panmictic populations have the some growth behavior. Furthermore, we show that global selection intensity depends(More)
—In this paper, we present quantitative models for the selection pressure of cellular evolutionary algorithms on regular one-and two-dimensional (2-D) lattices. We derive models based on probabilistic difference equations for synchronous and several asynchronous cell update policies. The models are validated using two customary selection methods: binary(More)
We study an extension of cellular automata to arbitrary interconnection topologies for the majority and the synchronization problems. By using an evolutionary algorithm, we show that small-world type network topologies consistently evolve from regular and random structures without being designed beforehand. These topologies have better performance than(More)
We investigate the performances of collective task-solving capabilities and the robust-ness of complex networks of automata using the density and synchronization problems as typical cases. We show by computer simulations that evolved Watts–Strogatz small-world networks have superior performance with respect to several kinds of scale-free graphs. In(More)
In this paper we investigate the properties of CEAs with populations structured as Watts–Strogatz small-world graphs and Albert–Barabási scale-free graphs as problem solvers, using several standard discrete optimization problems as a benchmark. The EA variants employed include self-adaptation of mutation rates. Results are compared with the corresponding(More)
In this chapter we study cellular evolutionary algorithms, a kind of decentralized heuristics, and the importance of their induced explo-ration/exploitation balance on different problems. It is shown that, by choosing synchronous or asynchronous update policies, the selection pressure, and thus the exploration/exploitation tradeoff, can be influenced(More)
— We study by computer simulation a population of individuals playing the prisoner's dilemma game. Each player has an invariable strategy (cooperate or defect) but the network of relationships between players is allowed to change over time following simple rules based on players' degree of satisfaction. The population almost always reaches a stable state(More)
The structure of a network dramatically affects the spreading phenomena unfolding upon it. The contact distribution of the nodes has long been recognized as the key ingredient in influencing the outbreak events. However, limited knowledge is currently available on the role of the weight of the edges on the persistence of a pathogen. At the same time, recent(More)