Andrei Dan Leca

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Evolutionary algorithms have become popular in the recent years as a general, simple, and robust technique that can be used when other optimization methods cannot be applied. Presently, there are a number of evolutionary/genetic algorithm libraries publicly available; however, they are not specifically designed for multiagent systems. The framework(More)
Learning can increase the flexibility and adaptability of the agents in a multiagent system. In this paper, we propose an automated system for solving classification and regression problems with the use of neural networks, where agents have three different learning algorithms and try to estimate a good network topology. We establish a competitive behavior(More)
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