Titlebook: Estimation of Distribution Algorithms; A New Tool for Evolu Pedro Larrañaga,Jose A. Lozano Book 2002 Springer Science+Business Media New Yo

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James R. Cullen,M. Melamud,K. HathawayEach individual obtained by simulation of the probability distribution learnt in each EDA generation represents a disjunction of a finite number of simple rules. This problem has been modeled to allow representations with different complexities. Experimental results comparing three types of EDAs —UM

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Crystalline Metal Oxide Catalystset of the network variables ., given some observations . This problem, also known as the ., is known to be NP-hard, so exact computation is not always possible. As partial abductive inference in Bayesian networks can be viewed as a combinatorial optimization problem, Genetic Algorithms have been suc