Parallel Problem Solving from Nature: 1st Workshop, PPSN I Dortmund, FRG, October 1–3, 1990 Proceedings

Introduction....Pages 1-2
Global convergence of genetic algorithms: A markov chain analysis....Pages 3-12
The theory of virtual alphabets....Pages 13-22
Towards an optimal mutation probability for genetic algorithms....Pages 23-32
An alternative Genetic Algorithm....Pages 33-37
An analysis of the interacting roles of population size and crossover in genetic algorithms....Pages 38-47
Gleam a system for simulated \"intuitive learning\"....Pages 48-54
Genetic algorithms and highly constrained problems: The time-table case....Pages 55-59
An evolution standing on the design of redundant manipulators....Pages 60-69
Redundant coding of an NP-complete problem allows effective Genetic Algorithm search....Pages 70-74
Circuit partitioning with genetic algorithms using a coding scheme to preserve the structure of a circuit....Pages 75-79
Genetic algorithms, production plan optimisation and scheduling....Pages 80-84
System identification using genetic algorithms....Pages 85-89
Conformational analysis of DNA using genetic algorithms....Pages 90-97
Operator-oriented genetic algorithm and its application to sliding block puzzle problem....Pages 98-103
A topology exploiting genetic algorithm to control dynamic systems....Pages 104-108
Genetic local search algorithms for the traveling salesman problem....Pages 109-116
Genetic programming artificial nervous systems artificial embryos and embryological electronics....Pages 117-123
Concept formation and decision tree induction using the genetic programming paradigm....Pages 124-128
On solving travelling salesman problems by genetic algorithms....Pages 129-133
Genetic algorithms and punctuated equilibria in VLSI....Pages 134-144
Implementing the genetic algorithm on transputer based parallel processing systems....Pages 145-149
Explicit parallelism of genetic algorithms through population structures....Pages 150-159
Parallel genetic packing of rectangles....Pages 160-164
Partitioning a graph with a parallel genetic algorithm....Pages 165-169
Solving the mapping-problem — Experiences with a genetic algorithm....Pages 170-175
Optimization using distributed genetic algorithms....Pages 176-185
Application of the Evolutionsstrategie to discrete optimization problems....Pages 187-192
A variant of evolution strategies for vector optimization....Pages 193-197
Application of evolution strategy in parallel populations....Pages 198-208
Global optimization by means of distributed evolution strategies....Pages 209-213
Solving sequential games with Boltzmann-learned tactics....Pages 215-220
Optimizing simulated annealing....Pages 221-225
Parallel Implementations Of Simulated Annealing....Pages 226-230
Error-free parallel implementation of simulated annealing....Pages 231-241
Trimm: A parallel processor for image reconstruction by simulated annealing....Pages 242-251
The response-time constraint in neural evolution....Pages 253-258
An artificial neural network representation for artificial organisms....Pages 259-263
Feature construction for back-propagation....Pages 264-268
Improved convergence rate of back-propagation with dynamic adaption of the learning rate....Pages 269-273
Performance evaluation of evolutionarily created neural network topologies....Pages 274-283
Optical image preprocessing for neural network classifier system....Pages 284-291
Gannet: Genetic design of a neural net for face recognition....Pages 292-296
The application of a genetic approach as an algorithm for neural networks....Pages 297-301
Genetic improvements of feedforward nets for approximating functions....Pages 302-306
Exploring adaptive agency III: Simulating the evolution of habituation and sensitization....Pages 307-313
A learning strategy for neural networks based on a modified evolutionary strategy....Pages 314-318
Genetic algorithms and the immune system....Pages 319-325
Selectionist categorization....Pages 326-330
A classifier system with integrated genetic operators....Pages 331-337
The fuzzy classifier system: Motivations and first results....Pages 338-342
Hints for adaptive problem solving gleaned from immune networks....Pages 343-354
A reactive robot navigation system based on a fluid dynamics metaphor....Pages 355-362
Transfer of natural metaphors to parallel problem solving applications....Pages 363-372
Modelling and simulation of distributed evolutionary search processes for function optimization....Pages 373-380
Parallel, decentralized spatial mapping for robot navigation and path planning....Pages 381-386
Ecological dynamics under different selection rules in distributed and iterated prisoner\'s dilemma game....Pages 387-394
Adaptation in signal spaces....Pages 395-404
A principle of minimum complexity in evolution....Pages 405-409
The emergence of data structures from local interactions....Pages 410-414
The view from the adaptive landscape....Pages 415-427
Boltzmann-, Darwin- and Haeckel-strategies in optimization problems....Pages 429-444
Optimizing complex problems by nature\'s algorithms: Simulated annealing and evolution strategy—a comparative study....Pages 445-454
Genetic Algorithms and evolution strategies: Similarities and differences....Pages 455-469
Building the ultimate machine: The emergence of artificial cognition....Pages 471-481