Frontiers of Evolutionary Computation
Springer Science & Business Media, Feb 29, 2004 - Computers - 271 pages
Frontiers of Evolutionary Computation brings together eleven contributions by international leading researchers discussing what significant issues still remain unresolved in the field of Evolutionary Computation (EC). They explore such topics as the role of building blocks, the balancing of exploration with exploitation, the modeling of EC algorithms, the connection with optimization theory and the role of EC as a meta-heuristic method, to name a few. The articles feature a mixture of informal discussion interspersed with formal statements, thus providing the reader an opportunity to observe a wide range of EC problems from the investigative perspective of world-renowned researchers. These prominent researchers include: -Heinz Mühlenbein, -Kenneth De Jong, -Carlos Cotta and Pablo Moscato, -Lee Altenberg, -Gary A. Kochenberger, Fred Glover, Bahram Alidaee and Cesar Rego, -William G. Macready, -Christopher R. Stephens and Riccardo Poli, -Lothar M. Schmitt, -John R. Koza, Matthew J. Street and Martin A. Keane, -Vivek Balaraman, -Wolfgang Banzhaf and Julian Miller. Frontiers of Evolutionary Computation is ideal for researchers and students who want to follow the process of EC problem-solving and for those who want to consider what frontiers still await their exploration.
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List of Tables Preface Contributing Authors
Towards memory based reasoning
Challenges and duties
Solving Combinatorial Optimization Problems via Reformulation
Stochastic analysis of cellular automata 12 1 12 2 The nonlinear voter model Stochastic analysis of one dimensional SCA Stochastic analysis of evolu...
CSchemas as Building Blocks
The Challenge Of Complexity
Wolfgang Banzhaf and Julian Miller 1 GP Basics and State of the
The Situation in Biology
Natures way to deal with complexity
What we can learn from Nature?
Problems in Optimization
Christopher R Stephens and Riccardo Poli
Asymptotic Convergence of Scaled Genetic Algorithms
The Challenge of Producing HumanCompetitive Results by Means
Case Based Reasoning
Other editions - View all
adaptation analysis application approach Artificial Intelligence asymptotic behavior binary Building Block C-Schema case-base case-based reasoning challenges complexity Computer Science convergence creatures crossover Davis and Principe defined discussed dynamics EC theory editors effective fitness eigenvalue equations evolution evolutionary algorithms Evolutionary Computation evolutionary systems finite population fitness function fitness landscape fitness selection framework genes genetic algorithms genetic and evolutionary genetic operators Genetic Programming Global Optimization Goldberg gorithms heuristic Holland human-competitive results infinite population model Koza Let denote linear machine learning Markov chain mathematical memory metaheuristics methods Morgan Kaufmann Mühlenbein mutation rate mutation-crossover organisms parameters Poli probabilistic probability distribution problem solving Proceedings ofthe proof Proposition quadratic rapid first hitting recombination representation retrieval rithms scaled genetic algorithm Schema theorem schemata Schmitt search space shows statement simulated annealing single-cutpoint solution stochastic matrix strings structure tabu search tion uniform populations variables vector Vose weak ergodicity