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List of contents
Contents Genetic Search Theory. D.E. Goldberg, P. Segrest, Finite Markov Chain Analysis of Genetic Algorithms. C.L. Bridges, D.E. Goldberg, An Analysis of Reproduction and Crossover in a Binary-Coded Genetic Algorithm. J.E. Baker, Reducing Bias and Inefficiency in the Selection Algorithm. T.H. Westerdale, Adaptive Search Operators I. Altruism in the Bucket Brigade. I. Stadnyk Schema Recombination in Pattern Recognition Problems. J.D. Schaffer, A. Morishima, An Adaptive Crossover Distribution Mechanism for Genetic Algorithms. D.E. Goldberg, J. Richardson, Representation Issues. Genetic Algorithms With Sharing for Multimodal Function Optimization. C.G. Shaefer, The ARGOT Strategy: Adaptive Representation Genetic Optimizer Technique. D.E. Goldberg, R.E. Smith, Nonstationary Function Optimization Using Genetic Algorithms With Dominance and Diploidy. H.J. Antonisse, K.S. Keller, Genetic Operators for High-Level Knowledge Representations. A.S. Bickel, R.W. Bickel, Keynote Address. Tree Structured Rules in Genetic Algorithms. J.H. Holland, Adaptive Search Operators II. Genetic Algorithms and Classifier Systems: Foundations and Future Directions. G.E. Liepins, M.R. Hilliard, M. Palmer, M. Morrow, Greedy Genetics. J.Y. Suh, D. Van Gucht, Incorporating Heuristic Information Into Genetic Search. D. Whitley, Using Reproductive Evaluation to Improve Genetic Search and Heuristic Discovery. D.J. Sirag, P.T. Weisser, Connectionism and Parallelism I. Toward a Unified Thermodynamic Genetic Operator. C.P. Dolan, M.G. Dyer, Toward the Evolution of Symbols. D.G. Oosthuizen, SUPERGRAN: A Connectionist Approach to Learning, Integrating, Genetic Algorithms and Graph Induction. G.G. Robertson, Parallel Implementation of Genetic Algorithms in a Classifier System. J.P. Cohoon, S.U. Hegde, W.N. Martin, D. Richards, Parallelism II. Punctuated Equilibria: A Parallel Genetic Algorithm. C.B. Pettey, M.R. Leuze, J.J. Grefenstette, A Parallel Genetic Algorithm. A.V. Sannier, II, E.D. Goodman, Genetic Learning Procedures in Distributed Environments. P. Jog, D. Van Gucht, Parallelisation of Probablistic Sequential Search Algorithms. R. Tanese, Credit Assignment and Learning. Parallel Genetic Algorithms for a Hypercube. R.L. Riolo, Bucket Brigade Performance: I. Long Sequences of Classifiers. R.L. Riolo, Bucket Brigade Performance: II. Default Hierarchies. J.J. Grefenstette, Multilevel Credit Assignment in a Genetic Learning System. K.A. De Jong, Applications I. On Using Genetic Algorithms to Search Program Spaces. D.P. Greene, S.F. Smith, A Genetic System for Learning Models of Consumer Choice. I.M. Oliver, D.J. Smith, J.R.C. Holland, A Study of Permutation Crossover Operators on the Traveling Salesman Problem. M.R. Hilliard, G.E. Liepins, M. Palmer, M. Morrow, J. Richardson, A Classifier Based System for Discovering Scheduling Heuristics. C. Fujiko, J. Dickinson, Applications II. Using the Genetic Algorithm to Generate LISP Source Code to Solve the Prisoner's Dilemma. V.V. Raghavan, B. Agarwal, Optimal Determination of User- Oriented Clusters: An Application for the Reproductive Plan. S.W. Wilson, The Genetic Algorithm and Biological Development. L. Davis, S. Coombs, Genetic Algorithms and Communication Link Speed Design: Theoretical Considerations. S. Coombs, L. Davis, Genetic Algorithms and Communication Link Speed Design: Constraints and Operators.
About the author
Edited by John J. Grefenstette, Naval Research Laboratory
Summary
First Published in 1987. This is the collected proceedings of the second International Conference on Genetic Algorithms held at the Massachusetts Institute of Technology, Cambridge, MA on the 28th to the 31st July 1987. With papers on Genetic search theory, Adaptive search operators, representation issues, connectionism and parallelism, credit assignment ad learning, and applications.
