The Evolution Arti?cielle cycle of conferences was originally initiated as a forum for the French-speaking evolutionary computation community. Previous EA m- tings were held in Toulouse (EA’94), Brest (EA’95, LNCS 1063), Nˆ?mes (EA’97, LNCS 1363), Dunkerque (EA’99, LNCS 1829), and ?nally, EA 2001 was hosted by the Universit´e de Bourgogne in the small town of Le Creusot, in an area of France renowned for its excellent wines. However, the EA conferences have been receiving more and more papers from the international community: this conference can be considered fully internat- nal, with 39submissions from non-francophonic countries on all ?ve continents, out of a total of 68. Out of these 68 papers, only 28 were presented orally (41%) due to the formula of the conference (single session with presentations of 30 minutes) that all participants seem to appreciate a lot. The Organizing Committee wishes to thank the members of the International Program Committee for their hard work (mainly due to the large number of submissions) and for the service they rendered to the community by ensuring the high scienti?c content of the papers presented. Actually, the overall quality of the papers presented was very high and all 28 presentations are included in this volume, grouped in 8 sections which more or less re?ect the organization of the oral session: 1. Invited Paper: P. Bentley gave a great talk on his classi?cation of int- disciplinary collaborations, and showed us some of his work with musicians and biologists.
Author(s): Peter J. Bentley (auth.), Pierre Collet, Cyril Fonlupt, Jin-Kao Hao, Evelyne Lutton, Marc Schoenauer (eds.)
Series: Lecture Notes in Computer Science 2310
Edition: 1
Publisher: Springer-Verlag Berlin Heidelberg
Year: 2002
Language: English
Pages: 374
Tags: Computation by Abstract Devices; Algorithm Analysis and Problem Complexity; Artificial Intelligence (incl. Robotics); Pattern Recognition; Numeric Computing
Why Biologists and Computer Scientists Should Work Together....Pages 3-15
Niching in Monte Carlo Filtering Algorithms....Pages 19-30
Measurement of Population Diversity....Pages 31-41
Prediction of Binary Sequences by Evolving Finite State Machines....Pages 42-53
Extending Selection Learning toward Fixed-Length d -Ary Strings....Pages 54-64
Markov Random Field Modelling of Royal Road Genetic Algorithms....Pages 65-76
Measuring the Spatial Dispersion of Evolutionary Search Processes: Application to Walksat....Pages 77-87
The Importance of Selection Mechanisms in Distribution Estimation Algorithms....Pages 91-103
Surrogate Deterministic Mutation: Preliminary Results....Pages 104-116
The Effects of Partial Restarts in Evolutionary Search....Pages 117-127
History and Immortality in Evolutionary Computation....Pages 128-139
Origins and Learnability of Syllable Systems: A Cultural Evolutionary Model....Pages 143-155
Evolution Strategy in Portfolio Optimization....Pages 156-167
Scatter Search for Graph Coloring....Pages 168-179
The Two Stage Continuous Parallel Flow Shop Problem with Limited Storage: Modeling and Algorithms....Pages 180-191
SAT, Local Search Dynamics and Density of States....Pages 192-204
A Multiobjective Evolutionary Algorithm for Car Front End Design....Pages 205-216
EASEA Comparisons on Test Functions: GALib versus EO....Pages 219-230
Evolving Objects: A General Purpose Evolutionary Computation Library....Pages 231-242
Backwarding: An Overfitting Control for Genetic Programming in a Remote Sensing Application....Pages 245-254
Avoiding the Bloat with Stochastic Grammar-Based Genetic Programming....Pages 255-266
Applying Boosting Techniques to Genetic Programming....Pages 267-278
Dual Evolutionary Optimization....Pages 281-294
Using Evolutionary Algorithms Incorporating the Augmented Lagrangian Penalty Function to Solve Discrete and Continuous Constrained Non-linear Optimal Control Problems....Pages 295-308
Cooperative Coevolution for Learning Fuzzy Rule-Based Systems....Pages 311-322
Evolving Cooperative Ecosystems: A Multi-agent Simulation of Deforestation Activities....Pages 323-337
The Impact of Environmental Structure on the Evolutionary Trajectories of a Foraging Agent....Pages 338-349
Learning as a Consequence of Selection....Pages 350-361
Coevolution and Evolving Parallel Cellular Automata-Based Scheduling Algorithms....Pages 362-373
