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Parallel Problem Solving from Nature - PPSN III: International Conference on Evolutionary Computation. The Third Conference on Parallel Problem Solving from Nature, Jerusalem, Israel, October 9 - 14, 1994. Proceedings / Edition 1

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More About This Textbook

Overview

This volume comprises the 61 revised refereed papers accepted for presentation at the ICEC/PPSN III conferences held jointly in Jerusalem, Israel in October 1994.
With the appearance of more and more powerful computers, there is increased interest in algorithms relying upon analogies to natural processes. This book presents a wealth of new theoretical and experimental results on artificial problem solving by applying evolutionary computation metaphors, including evolution strategies, evolutionary programming, genetic algorithms, genetic programming, and classifier systems. Topics such as simulated annealing, immune networks, neural networks, fuzzy systems, and complex, real-world optimization problems are also treated.

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Product Details

  • ISBN-13: 9783540584841
  • Publisher: Springer Berlin Heidelberg
  • Publication date: 10/27/1994
  • Series: Lecture Notes in Computer Science Series , #866
  • Edition description: 1994
  • Edition number: 1
  • Pages: 647
  • Product dimensions: 9.21 (w) x 6.14 (h) x 1.41 (d)

Table of Contents

Introduction 1
Lamarckian Evolution, The Baldwin Effect and Function Optimization 6
Control of Parallel Population Dynamics by Social-Like Behavior of GA-Individuals 16
Studying Genotype-Phenotype Interactions: A Model of the Evolution of the Cell Regulation Network 26
A Diploid Genetic Algorithm for Preserving Population Diversity - Pseudo-Meiosis GA 36
Co-evolutionary Constraint Satisfaction 46
Towards a Theory of 'Evolution Strategies': Results for (1+,[lambda])-Strategies on (Nearly) Arbitrary Fitness Functions 58
Advanced Correlation Analysis of Operators for the Traveling Salesman Problem 68
Genetic Algorithms with Multi-parent Recombination 78
On the Mean Convergence Time of Evolutionary Algorithms without Selection and Mutation 88
Estimating the Heritability by Decomposing the Genetic Variance 98
Analyzing Hyperplane Synthesis in Genetic Algorithms Using Clustered Schemata 108
Convergence Models of Genetic Algorithm Selection Schemes 119
Optimal Population Size under Constant Computation Cost 130
An Evolutionary Algorithm for Integer Programming 139
Long Path Problems 149
Evolution Strategies on Noisy Functions: How to Improve Convergence Properties 159
Selection Schemes with Spatial Isolation for Genetic Optimization 170
A Modified Edge Recombination Operator for the Travelling Salesman Problem 180
Step-size Adaptation Based on Non-local Use of Selection Information 189
Strategy Adaptation by Competing Subpopulations 199
Controlling Crossover through Inductive Learning 209
Derivative Operators for Preference Predicate Evolution 219
Adaptive Crossover Using Automata 229
Controlling Dynamics of GA through Filtered Evaluation Function 239
A Cooperative Coevolutionary Approach to Function Optimization 249
A Fuzzy Classifier System Using the Pittsburgh Approach 260
Q-Learning in Evolutionary Rule-based Systems 270
On the Complexity of Learning in Classifier Systems 280
A Representation Scheme to Perform Program Induction in a Canonical Genetic Algorithm 292
Genetic Programming with Local Hill-Climbing 302
Dynamic Training Subset Selection for Supervised Learning in Genetic Programming 312
Genotype-Phenotype-Mapping and Neutral Variation - A Case Study in Genetic Programming 322
Genetic L-System Programming 334
A Genetic Algorithm Discovers Particle-Based Computation in Cellular Automata 344
Simulation of Exaptive Behaviour 354
Artificial Spacing Patterns in a Network of Interacting Celloids 365
Diffuse Pattern Learning with Fuzzy ARTMAP and PASS 376
Different Learning Algorithms for Neural Networks - A Comparative Study 386
Program Search with a Hierarchical Variable Length Representation: Genetic Programming, Simulated Annealing and Hill Climbing 397
Problem-Independent Parallel Simulated Annealing Using Selection and Migration 408
Parallel Optimization of Evolutionary Algorithms 418
Parallel Simulated Annealing and Genetic Algorithms: A Space of Hybrid Methods 428
ENZO-M - A Hybrid Approach for Optimizing Neural Networks by Evolution and Learning 440
Genetic Lander: An Experiment in Accurate Neuro-Genetic Control 452
Effects of Occam's Razor in Evolving Sigma-Pi Neural Nets 462
Designing Neural Networks by Adaptively Building Blocks in Cascades 472
Hybrid Adaptive Heuristic Critic Architectures for Learning in Mazes with Continuous Search Spaces 482
Mutation Operators for Structure Evolution of Neural Networks 492
Implementation of Standard Genetic Algorithm on MIMD Machines 504
Loosely Coupled Distributed Genetic Algorithms 514
Applying Evolvable Hardware to Autonomous Agents 524
Genetic Algorithms on LAN-Message Passing Architectures Using PVM: Application to the Routing Problem 534
Genetic Algorithm Based Design Optimization of CMOS VLSI Circuits 546
Improving Evolutionary Timetabling with Delta Evaluation and Directed Mutation 556
Genetic Improvement of Railway Timetables 566
Using a Genetic Algorithm to Search for the Representational Bias of a Collective Reinforcement Learner 576
An Evolutionary Algorithm for the Routing of Multi-Chip Modules 588
System Design under Uncertainty: Evolutionary Optimization of the Gravity Probe-B Spacecraft 598
Soft Selection in D-optimal Designs 608
The Weighted Graph Bi-Partitioning Problem: A Look at GA Performance 617
RPL2: A Language and Parallel Framework for Evolutionary Computing 628
Subject Index 639
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