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We heuristically solve an evacuation problem with limited capacity shelters. An evolutionary learning algorithm is developed for the combined route- and shelter-assignment problem. It is complemented with a heuristic method for the fair minimization of she ...
Around three quarters of global resource consumption takes place in urban settlements, with corresponding adverse environmental consequences. According to population forecasts this situation will be exacerbated during the coming years. It is therefore impe ...
The integration of modulatory neurons into evolutionary artificial neural networks is proposed here. A model of modulatory neurons was devised to describe a plasticity mechanism at the low level of synapses and neurons. No initial assumptions were made on ...
Designing effective behavioral controllers for mobile robots can be difficult and tedious; this process can be circumvented by using unsupervised learning techniques which allow robots to evolve their own controllers in an automated fashion. In multi-robot ...
Bio-inspired electronic circuits have the potential to address some of the shortcomings of conventional electronic circuits, such as lack of applicability to ill-defined problems, of robustness, or of adaptivity to unexpectedly changing environments. Bio-i ...
A major challenge to understanding behavior is how the nervous system allows the learning of behavioral sequences that can occur over arbitrary timescales, ranging from milliseconds up to seconds, using a fixed millisecond learning rule. This article descr ...
The significant increase in the available computational power that took place in recent decades has been accompanied by a growing interest in the application of the evolutionary approach to the synthesis of many kinds of systems and, in particular, to the ...
In this paper we address the problem of defining a measure of diversity for a population of individuals whose genome can be subjected to major reorganizations during the evolutionary process. To this end, we introduce a measure of diversity for populations ...
Designing effective behavioral controllers for mobile robots can be difficult and tedious; this process can be circumvented by using unsupervised learning techniques which allow robots to evolve their own controllers online in an automated fashion. In mult ...
The CEPA, an Evolutionary Algorithm that preserves diversity by finding clusters in the population, has had its convergence performance improved by a technique tentatively called ‘evolutionary operator selection’. Performance is compared to results found i ...
