Evolutionary Computation Implementations

[1]  Terence C. Fogarty,et al.  Varying the Probability of Mutation in the Genetic Algorithm , 1989, ICGA.

[2]  Gilbert Syswerda,et al.  Simulated Crossover in Genetic Algorithms , 1992, FOGA.

[3]  W. Spears,et al.  On the Virtues of Parameterized Uniform Crossover , 1995 .

[4]  Kalmanje Krishnakumar,et al.  Micro-Genetic Algorithms For Stationary And Non-Stationary Function Optimization , 1990, Other Conferences.

[5]  Marco Dorigo,et al.  Alecsys: A Parallel Laboratory for Learning Classifier Systems , 1991, ICGA.

[6]  William M. Spears,et al.  Crossover or Mutation? , 1992, FOGA.

[7]  Byung Ro Moon,et al.  Analyzing Hyperplane Synthesis in Genetic Algorithms Using Clustered Schemata , 1994, PPSN.

[8]  James R. Levenick,et al.  Metabits: Generic Endogenous Crossover Control , 1995, International Conference on Genetic Algorithms.

[9]  Thomas Bäck,et al.  An Overview of Evolutionary Algorithms for Parameter Optimization , 1993, Evolutionary Computation.

[10]  Bernard Manderick,et al.  Fine-Grained Parallel Genetic Algorithms , 1989, ICGA.

[11]  Larry J. Eshelman,et al.  Biases in the Crossover Landscape , 1989, ICGA.

[12]  Larry J. Eshelman,et al.  Productive Recombination and Propagating and Preserving Schemata , 1994, FOGA.

[13]  Patrick D. Surry,et al.  Fitness Variance of Formae and Performance Prediction , 1994, FOGA.

[14]  Stephen F. Smith,et al.  Flexible Learning of Problem Solving Heuristics Through Adaptive Search , 1983, IJCAI.

[15]  David E. Goldberg,et al.  Sizing Populations for Serial and Parallel Genetic Algorithms , 1989, ICGA.

[16]  Katsunori Shimohara,et al.  Development and Evolution of Hardware Behaviors , 1995, Towards Evolvable Hardware.

[17]  Hiroaki Kitano,et al.  GA-1: A Parallel Associative Memory Processor for Rule Learning with Genetic Algorithms , 1991, ICGA.

[18]  Marco Dorigo,et al.  Alecsys and the AutonoMouse: Learning to control a real robot by distributed classifier systems , 2004, Machine Learning.

[19]  D. J. Smith,et al.  A Study of Permutation Crossover Operators on the Traveling Salesman Problem , 1987, ICGA.

[20]  Bernard Manderick,et al.  A Massively Parallel Genetic Algorithm: Implementation and First Analysis , 1991, ICGA.

[21]  Hideyuki Takagi,et al.  Dynamic Control of Genetic Algorithms Using Fuzzy Logic Techniques , 1993, ICGA.

[22]  Martina Gorges-Schleuter,et al.  ASPARAGOS An Asynchronous Parallel Genetic Optimization Strategy , 1989, ICGA.

[23]  Hiroaki Kitano,et al.  The IXM2 parallel associative processor for AI , 1994, Computer.

[24]  Kenneth A. De Jong,et al.  Genetic Algorithms are NOT Function Optimizers , 1992, FOGA.

[25]  Kenneth A. De Jong,et al.  An Analysis of the Interacting Roles of Population Size and Crossover in Genetic Algorithms , 1990, PPSN.

[26]  Byung Ro Moon,et al.  Exploiting synergies of multiple crossovers: initial studies , 1995, Proceedings of 1995 IEEE International Conference on Evolutionary Computation.

[27]  Bryant A. Julstrom,et al.  What Have You Done for Me Lately? Adapting Operator Probabilities in a Steady-State Genetic Algorithm , 1995, ICGA.

[28]  Masayuki Yanagiya,et al.  A Simple Mutation-Dependent Genetic Algorithm , 1993, ICGA.

[29]  John J. Grefenstette,et al.  A Parallel Genetic Algorithm , 1987, ICGA.

[30]  Reinhard Männer,et al.  Investigation of the M-Heuristic for Optimal Mutation Probabilities , 1992, Parallel Problem Solving from Nature.

[31]  William M. Spears,et al.  Adapting Crossover in Evolutionary Algorithms , 1995, Evolutionary Programming.

[32]  Hitoshi Iba,et al.  Evolvable hardware , 1994 .

[33]  Gilbert Syswerda,et al.  Uniform Crossover in Genetic Algorithms , 1989, ICGA.

[34]  Jan J. Mulawka,et al.  A New Class of the Crossover Operators for the Numerical Optimization , 1995, International Conference on Genetic Algorithms.

[35]  Reinhard Männer,et al.  Towards an Optimal Mutation Probability for Genetic Algorithms , 1990, PPSN.

[36]  L. Darrell Whitley,et al.  Serial and Parallel Genetic Algorithms as Function Optimizers , 1993, ICGA.

[37]  Thomas Bäck,et al.  The Interaction of Mutation Rate, Selection, and Self-Adaptation Within a Genetic Algorithm , 1992, PPSN.

[38]  John Dickinson,et al.  Using the Genetic Algorithm to Generate LISP Source Code to Solve the Prisoner's Dilemma , 1987, ICGA.

[39]  Kirk Twardowski,et al.  An associative architecture for genetic algorithm-based machine learning , 1994, Computer.

[40]  Robert E. Smith,et al.  Adaptively Resizing Populations: An Algorithm and Analysis , 1993, ICGA.

[41]  Lawrence Davis,et al.  Applying Adaptive Algorithms to Epistatic Domains , 1985, IJCAI.

[42]  Rajarshi Das,et al.  A Study of Control Parameters Affecting Online Performance of Genetic Algorithms for Function Optimization , 1989, ICGA.

[43]  Thomas Bäck,et al.  Evolution Strategies on Noisy Functions: How to Improve Convergence Properties , 1994, PPSN.

[44]  Nicholas J. Radcliffe,et al.  Forma Analysis and Random Respectful Recombination , 1991, ICGA.

[45]  Heinz Mühlenbein,et al.  How Genetic Algorithms Really Work: Mutation and Hillclimbing , 1992, PPSN.

[46]  Günter Rudolph,et al.  Contemporary Evolution Strategies , 1995, ECAL.

[47]  Justinian P. Rosca,et al.  Genetic Programming Exploratory Power and the Discovery of Functions , 1995, Evolutionary Programming.

[48]  Ellis Horowitz,et al.  Fundamentals of Computer Algorithms , 1978 .

[49]  Lee Altenberg,et al.  The Schema Theorem and Price's Theorem , 1994, FOGA.

[50]  Larry J. Eshelman,et al.  On Crossover as an Evolutionarily Viable Strategy , 1991, ICGA.

[51]  David B. Fogel,et al.  Evolving neurocontrollers using evolutionary programming , 1994, Proceedings of the First IEEE Conference on Evolutionary Computation. IEEE World Congress on Computational Intelligence.

[52]  Adrian Thompson,et al.  Evolving Electronic Robot Controller that Exploit Hardware Resources , 1995, ECAL.

[53]  Lawrence Davis,et al.  Adapting Operator Probabilities in Genetic Algorithms , 1989, ICGA.

[54]  M. Fischetti,et al.  A hybrid algorithm for finding thekth smallest ofn elements in O(n) time , 1988 .

[55]  David E. Goldberg,et al.  Genetic Algorithms and the Variance of Fitness , 1991, Complex Syst..

[56]  J. David Schaffer,et al.  An Adaptive Crossover Distribution Mechanism for Genetic Algorithms , 1987, ICGA.

[57]  Heinz Mühlenbein,et al.  Parallel Genetic Algorithms, Population Genetics, and Combinatorial Optimization , 1989, Parallelism, Learning, Evolution.

[58]  L. Darrell Whitley,et al.  A Comparison of Genetic Sequencing Operators , 1991, ICGA.

[59]  Isamu Kajitani,et al.  Hardware Evolution at Function Level , 1996, PPSN.

[60]  Lashon B. Booker,et al.  Recombination Distributions for Genetic Algorithms , 1992, FOGA.

[61]  Alden H. Wright,et al.  Genetic Algorithms for Real Parameter Optimization , 1990, FOGA.

[62]  David E. Goldberg,et al.  Alleles, loci and the traveling salesman problem , 1985 .

[63]  James E. Baker,et al.  Reducing Bias and Inefficienry in the Selection Algorithm , 1987, ICGA.

[64]  Byung Ro Moon,et al.  On Multi-Dimensional Encoding/Crossover , 1995, ICGA.

[65]  G. Cain,et al.  Genetic algorithm processor for adaptive IIR filters , 1995, Proceedings of 1995 IEEE International Conference on Evolutionary Computation.