منابع مشابه
Maintaining Diversity in Genetic Search
Genetic adaptive algorithms provide an efficient way to search large function spaces, and are increasingly being used in learning systems. One problem plaguing genetic learning algorithms is premature convergence, or convergence of the pool of active structures to a suboptimal point in the space being searched. An improvement to the standard genetic adaptive algorithm is presented which guarant...
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Niching techniques for evolutionary algorithms are aimed at maintaining the diversity through forming subpopulations (species) in multi-modal domains. Similar techniques may be applied to evolutionary multi-agent systems, which provide a decentralised model of evolution. In this paper a specific EMAS realisation is presented, in which the new species formation occurs as a result of co-evolution...
متن کاملMaintaining Genetic Diversity in Bacterial Evolutionary Algorithm
The Bacterial Evolutionary Algorithm (BEA) is a relatively new type of evolutionary algorithm and shows the typical phenomena of stochastic optimization methods. Two of these phenomena: premature convergence and low convergence speed near the optimum are often in connection with the low genetic diversity of the population. Variation of genetic diversity in the original BEA and in its three para...
متن کاملMaintaining Population Diversity By Minimizing Mutual Information
Based on negative correlation learning [1] and evolutionary learning, evolutionary ensembles with negative correlation learning (EENCL) was proposed for learning and designing of neural network ensembles [2]. The idea of EENCL is to regard the population of neural networks as an ensemble, and the evolutionary process as the design of neural network ensembles. EENCL used a tness sharing based on...
متن کاملMaintaining Diversity in Population of Evolved Models
This paper deals with creation of models by means of evolutionary algorithms, particularly with maintaining diversity of population using niching methods. Niching algorithms are known for their ability to search for more optima simultaneously. This is done by splitting the population of models into separate species. Species protect promising but yet not fully developed models. Search for more o...
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ژورنال
عنوان ژورنال: Science
سال: 2009
ISSN: 0036-8075,1095-9203
DOI: 10.1126/science.325_12d