Evolutionary Computation, Volume 13

Volume 13, Number 1, Spring 2005

• Marc Schoenauer:
  Editorial Introduction.
  
• Pedro Larrañaga, José Antonio Lozano:
  Editorial Introduction Special Issue on Estimation of Distribution Algorithms.
  
• Heinz Mühlenbein, Robin Höns:
  The Estimation of Distributions and the Minimum Relative Entropy Principle. 1-27
  
• Marcus Gallagher, Marcus R. Frean:
  Population-Based Continuous Optimization, Probabilistic Modelling and Mean Shift. 29-42
  
• José Manuel Peña, José Antonio Lozano, Pedro Larrañaga:
  Globally Multimodal Problem Optimization Via an Estimation of Distribution Algorithm Based on Unsupervised Learning of Bayesian Networks. 43-66
  
• Roberto Santana:
  Estimation of Distribution Algorithms with Kikuchi Approximations. 67-97
  
• Jonathan L. Shapiro:
  Drift and Scaling in Estimation of Distribution Algorithms. 99-123
  
• Yong Gao, Joseph C. Culberson:
  Space Complexity of Estimation of Distribution Algorithms. 125-143
  

Volume 13, Number 2, Summer 2005

• Marc Schoenauer:
  Editorial Introduction.
  
• Simon M. Garrett:
  How Do We Evaluate Artificial Immune Systems? 145-177
  
• Matthew Glickman, Justin Balthrop, Stephanie Forrest:
  A Machine Learning Evaluation of an Artificial Immune System. 179-212
  
• Marco Tomassini, Leonardo Vanneschi, Philippe Collard, Manuel Clergue:
  A Study of Fitness Distance Correlation as a Difficulty Measure in Genetic Programming. 213-239
  
• Jianjun Hu, Erik D. Goodman, Kisung Seo, Zhun Fan, Rondal Rosenberg:
  The Hierarchical Fair Competition (HFC) Framework for Sustainable Evolutionary Algorithms. 241-277
  

Volume 13, Number 3, Fall 2005

• Marc Schoenauer:
  Editorial Introduction.
  
• Ying-Ping Chen, David E. Goldberg:
  Convergence Time for the Linkage Learning Genetic Algorithm. 279-302
  
• Peter Dauscher, Thomas Uthmann:
  Self-Organized Modularization in Evolutionary Algorithms. 303-328
  
• Lauren M. Clevenger, Lauren Ferguson, William E. Hart:
  A Filter-Based Evolutionary Algorithm for Constrained Optimization. 329-352
  
• Laura A. McLay, David E. Goldberg:
  Efficient Genetic Algorithms Using Discretization Scheduling. 353-385
  
• Mihai Oltean:
  Evolving Evolutionary Algorithms Using Linear Genetic Programming. 387-410
  

Volume 13, Number 4, Winter 2005

• Thomas Jansen, Kenneth A. De Jong, Ingo Wegener:
  On the Choice of the Offspring Population Size in Evolutionary Algorithms. 413-440
  
• Günther R. Raidl, Jens Gottlieb:
  Empirical Analysis of Locality, Heritability and Heuristic Bias in Evolutionary Algorithms: A Case Study for the Multidimensional Knapsack Problem. 441-475
  
• Allan Tucker, Jason Crampton, Stephen Swift:
  RGFGA: An Efficient Representation and Crossover for Grouping Genetic Algorithms. 477-499
  
• Kalyanmoy Deb, Manikanth Mohan, Shikhar Mishra:
  Evaluating the epsilon-Domination Based Multi-Objective Evolutionary Algorithm for a Quick Computation of Pareto-Optimal Solutions. 501-525
  
• Dario Floreano, Mototaka Suzuki, Claudio Mattiussi:
  Active Vision and Receptive Field Development in Evolutionary Robots. 527-544
  
• Hugo de Garis:
  Conference Review: Evolvable Hardware 2005. 545-550