Zohar Ganon

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Network Management Systems are often challenged by the need to manage networks comprised of a very large number of elements. Effective testing of performance, capacity and stability of these management systems often requires significant and, at times, cost-prohibitive investment in equipment and computing resources. This paper presents a method which(More)
Neurocontroller minimization is beneficial for constructing small parsimonious networks that permit a better understanding of their workings. This paper presents a novel, Evolutionary Network Minimization (ENM) algorithm which is applied to fully recurrent neurocontrollers. ENM is a simple, standard genetic algorithm with an additional step in which small(More)
This study presents a new evolutionary network minimization (ENM) algorithm. Neurocontroller minimization is beneficial for finding small parsimonious networks that permit a better understanding of their workings. The ENM algorithm is specifically geared to an evolutionary agents setup, as it does not require any explicit supervised training error, and is(More)
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