Simulated evolution and learning

Simulated Evolution and Learning: Second Asia-Pacific Conference on Simulated Evolution and Learning, SEAL’98 Canberra, Australia, November 24–27, 1998 Selected Papers<br />Author: Bob McKay, Xin Yao, Charles S. Newton, Jong-Hwan Kim, Takeshi Furuhashi<br /> Published by Springer Berlin Heidelberg<br /> ISBN: 978-3-540-65907-5<br /> DOI: 10.1007/3-540-48873-1<br /><br />Table of Contents:<p></p><ul><li>Natural Computation
</li><li>Multiple Lagrange Multiplier Method for Constrained Evolutionary Optimization
</li><li>Robust Evolution Strategies
</li><li>Hybrid Genetic Algorithm for Solving the p-Median Problem
</li><li>Correction of Reflection Lines Using Genetic Algorithms
</li><li>Adaptation under Changing Environments with Various Rates of Inheritance of Acquired Characters
</li><li>Dynamic Control of Adaptive Parameters in Evolutionary Programming
</li><li>Information Operator Scheduling by Genetic Algorithms
</li><li>Solving Radial Topology Constrained Problems with Evolutionary Algorithms
</li><li>Automating Space Allocation in Higher Education
</li><li>Application of Genetic Algorithm and k-Nearest Neighbour Method in Medical Fraud Detection
</li><li>Evolution of Reference Sets in Nearest Neighbor Classification
</li><li>Investigation of a Cellular Genetic Algorithm that Mimics Landscape Ecology
</li><li>Quantifying Neighborhood Preservation: Joint Properties of Evolutionary and Unsupervised Neural Learning
</li><li>Neural Networks and Evolutionary Algorithms for the Prediction of Thermodynamic Properties for Chemical Engineering
</li><li>Evolving FPGA Based Cellular Automata
</li><li>Asynchronous Island Parallel GA Using Multiform Subpopulations
</li><li>Multiple Sequence Alignment Using Parallel Genetic Algorithms
</li><li>Evolving Logic Programs to Classify Chess-Endgame Positions
</li><li>Genetic Programming with Active Data Selection</li></ul>