Simulated Evolution and Learning: Second Asia-Pacific Conference on Simulated Evolution and Learning, SEAL'98, Canberra, Australia, November 24-27, 1998 Selected Papers / Edition 1

by Bob McKay, Xin Yao, Charles S. Newton, Jong-Hwan Kim, Takeshi Furuhashi

Overview

This volume contains selected papers presented at the Second Asia-Paci c C- ference on Simulated Evolution and Learning (SEAL’98), from 24 to 27 Nov- ber 1998, in Canberra, Australia. SEAL’98 received a total of 92 submissions (67 papers for the regular sessions and 25 for the applications sessions). All papers were reviewed by three independent reviewers. After review, 62 papers were - cepted for oral presentation and 13 for poster presentation. Some of the accepted papers were selected for inclusion in this volume. SEAL’98 also featured a fully refereed special session on Evolutionary Computation in Power Engineering - ganised by Professor Kit Po Wong and Dr Loi Lei Lai. Two of the ve accepted papers are included in this volume. The papers included in these proceedings cover a wide range of topics in simulated evolution and learning, from self-adaptation to dynamic modelling, from reinforcement learning to agent systems, from evolutionary games to e- lutionary economics, and from novel theoretical results to successful applications, among others. SEAL’98 attracted 94 participants from 14 di erent countries, namely A- tralia, Belgium, Brazil, Germany, Iceland, India, Japan, South Korea, New Z- land, Portugal, Sweden, Taiwan, UK and the USA. It had three distinguished international scientists as keynote speakers, giving talks on natural computation (Hans-Paul Schwefel), reinforcement learning (Richard Sutton), and novel m- els in evolutionary design (John Gero). More information about SEAL’98 is still available at http://www.cs.adfa.edu.au/conference/seal98/.

Product Details

ISBN-13:	9783540659075
Publisher:	Springer Berlin Heidelberg
Publication date:	07/20/1999
Series:	Lecture Notes in Computer Science , #1585
Edition description:	1999
Pages:	478
Product dimensions:	6.10(w) x 9.25(h) x (d)

Table of Contents

Natural Computation.- Multiple Lagrange Multiplier Method for Constrained Evolutionary Optimization.- Robust Evolution Strategies.- Hybrid Genetic Algorithm for Solving the p-Median Problem.- Correction of Reflection Lines Using Genetic Algorithms.- Adaptation under Changing Environments with Various Rates of Inheritance of Acquired Characters.- Dynamic Control of Adaptive Parameters in Evolutionary Programming.- Information Operator Scheduling by Genetic Algorithms.- Solving Radial Topology Constrained Problems with Evolutionary Algorithms.- Automating Space Allocation in Higher Education.- Application of Genetic Algorithm and k-Nearest Neighbour Method in Medical Fraud Detection.- Evolution of Reference Sets in Nearest Neighbor Classification.- Investigation of a Cellular Genetic Algorithm that Mimics Landscape Ecology.- Quantifying Neighborhood Preservation: Joint Properties of Evolutionary and Unsupervised Neural Learning.- Neural Networks and Evolutionary Algorithms for the Prediction of Thermodynamic Properties for Chemical Engineering.- Evolving FPGA Based Cellular Automata.- Asynchronous Island Parallel GA Using Multiform Subpopulations.- Multiple Sequence Alignment Using Parallel Genetic Algorithms.- Evolving Logic Programs to Classify Chess-Endgame Positions.- Genetic Programming with Active Data Selection.- Evolutionary Programming-Based Uni-vector Field Method for Fast Mobile Robot Navigation.- Evolution with Learning Adaptive Functions.- Modelling Plant Breeding Programs as Search Strategies on a Complex Response Surface.- Generating Equations with Genetic Programming for Control of a Movable Inverted Pendulum.- A Hybrid Tabu Search Algorithm for the Nurse Rostering Problem.- Reinforcement Learning: Past, Present and Future.- A Reinforcement Learning with Condition Reduced Fuzz Rules.- Generality and Conciseness of Submodels in Hierarchical Fuzzy Modeling.- Using Evolutionary Programming to Optimize the Allocation of Surveillance Assets.- Applying the Evolutionary Neural Networks with Genetic Algorithms to Control a Rolling Inverted Pendulum.- Evolving Cooperative Actions Among Heterogeneous Agents by an Evolutionary Programming Method.- Cooperative Works for Welfare Agent Robot and Human Using Chaotic Evolutionary Computation.- Evolutionary Computation for Intelligent Agents Based on Chaotic Retrieval and Soft DNA.- A Study of Bayesian Clustering of a Document Set Based on GA.- An Evolutionary Approach in Quantitative Spectroscopy.- Evolutionary Recognition of Features from CAD Data.- Modeling Strategies as Generous and Greedy in Prisoner’s Dilemma Like Games.- Using Genetic Algorithms to Simulate the Evolution of an Oligopoly Game.- An Evolutionary Study on Cooperation in N-person Iterated Prisoner’s Dilemma Game.- Simulating a N-person Multi-stage Game for Making a State.- Learning from Linguistic Rules and Rule Extraction for Function Approximation by Neural Networks.- Can a Niching Method Locate Multiple Attractors Embedded in the Hopfield Network?.- Time Series Prediction by Using Negatively Correlated Neural Networks.- Animating the Evolution Process of Genetic Algorithms.- Analysis on the Island Model Parallel Genetic Algorithms for the Genetic Drifts.- A Paradox of Neural Encoders and Decoders or Why Don’t We Talk Backwards?.- Continuous Optimization Using Elite Genetic Algorithms With Adaptive Mutations.- Evolutionary Systems Applied to the Synthesis of a CPU Controller.- Novel Models in Evolutionary Designing.- Co-evolution, Determinism and Robustness.- Co-operative Evolution of a Neural Classifier andFeature Subset.- Optimal Power Flow Method Using Evolutionary Programming.- Grammatical Development of Evolutionary Modular Neural Networks.- Hybridized Neural Network and Genetic Algorithms for Solving Nonlinear Integer Programming Problem.- Evolution of Gene Coordination Networks.- Adaptive Simulation: An Implementation Framework.- A Model of Mutual Associative Memory for Simulations of Evolution and Learning.- The Application of Cellular Automata to the Consumer’s Theory: Simulating a Duopolistic Market.- Object-Oriented Genetic Algorithm Based Artificial Neural Network for Load Forecasting.