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GENETIC OPERATORS USING VIRAL MODELS
AN EVOLUTIONARY AND COOPERATIVE AGENTS MODEL FOR OPTIMIZATION
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adaptive amoeba antibodies antigen applied approach Artificial automata behavior cells chromosome constraints convergence crossover operator defined described dynamic encoding equation error evaluation evolution evolution strategies evolutionary algorithms evolved example Figure fitness function fitness sharing fitness value function smoothing fuzzy classifier system fuzzy if-then rules fuzzy sets gene Genetic Algorithms genetic operators Genetic Programming genotype given global optimum idiotope IEEE immune system immunobot individual initial population input interactive inversion LOGENPRO logic grammar logic programs Machine Learning method mobile robot mutation operator neural networks node objective function obtained offspring optimization organism-A organisms output paper parameters paratope parent patterns performance Proc produced proposed random randomly represent S-expression search space Section selection self-replicating shown shows simulation slime moulds solution solve step strategy string structure Table technique tion total number travelling salesman problem tree University variables vector