The evolution of genetic representations andmodularadapta tion Dissertation zur Erlangung des Grades eines Doktors der Naturwissenschaften in der Fakultat fur Physik und Astronomie der Ruhr-Universitat Bochum

[1]  Christian M. Reidys,et al.  Combinatorial Landscapes , 2002, SIAM Rev..

[2]  G. Wagner,et al.  The topology of the possible: formal spaces underlying patterns of evolutionary change. , 2001, Journal of theoretical biology.

[3]  Kenji Fukumizu,et al.  Adaptive Method of Realizing Natural Gradient Learning for Multilayer Perceptrons , 2000, Neural Computation.

[4]  Andrew G. Barto,et al.  Reinforcement learning , 1998 .

[5]  J. Monod,et al.  Genetic regulatory mechanisms in the synthesis of proteins. , 1961, Journal of molecular biology.

[6]  Fuad Rahman,et al.  Serial Combination of Multiple Experts: A Unified Evaluation , 1999, Pattern Analysis & Applications.

[7]  Jim Smith,et al.  Operator and parameter adaptation in genetic algorithms , 1997, Soft Comput..

[8]  J. Pollack,et al.  A computational model of symbiotic composition in evolutionary transitions. , 2003, Bio Systems.

[9]  Marc Toussaint,et al.  Self-adaptive exploration in evolutionary search , 2001, ArXiv.

[10]  Jordan B. Pollack,et al.  Evolving L-systems to generate virtual creatures , 2001, Comput. Graph..

[11]  Lee Altenberg,et al.  Evolving better representations through selective genome growth , 1994, Proceedings of the First IEEE Conference on Evolutionary Computation. IEEE World Congress on Computational Intelligence.

[12]  G. Wagner,et al.  A POPULATION GENETIC THEORY OF CANALIZATION , 1997, Evolution; international journal of organic evolution.

[13]  Hiroaki Kitano,et al.  Designing Neural Networks Using Genetic Algorithms with Graph Generation System , 1990, Complex Syst..

[14]  Przemyslaw Prusinkiewicz,et al.  The Algorithmic Beauty of Plants , 1990, The Virtual Laboratory.

[15]  R. French Catastrophic forgetting in connectionist networks , 1999, Trends in Cognitive Sciences.

[16]  Peter Nordin,et al.  Complexity Compression and Evolution , 1995, ICGA.

[17]  Shun-Ichi Amari,et al.  Mathematical methods of neurocomputing , 1993 .

[18]  M. Kimura,et al.  The neutral theory of molecular evolution. , 1983, Scientific American.

[19]  T. Back,et al.  On the behavior of evolutionary algorithms in dynamic environments , 1998, 1998 IEEE International Conference on Evolutionary Computation Proceedings. IEEE World Congress on Computational Intelligence (Cat. No.98TH8360).

[20]  Marc Toussaint,et al.  Demonstrating the Evolution of Complex Genetic Representations: An Evolution of Artificial Plants , 2003, GECCO.

[21]  G. Wagner,et al.  Epistasis and the mutation load: a measurement-theoretical approach. , 2001, Genetics.

[22]  John H. Holland,et al.  Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence , 1992 .

[23]  H. Akaike A new look at the statistical model identification , 1974 .

[24]  John H. Holland,et al.  Building Blocks, Cohort Genetic Algorithms, and Hyperplane-Defined Functions , 2000, Evolutionary Computation.

[25]  Bernhard Sendhoff,et al.  A Condition for the Genotype-Phenotype Mapping: Causality , 1997, ICGA.

[26]  Shun-ichi Amari,et al.  Natural Gradient Works Efficiently in Learning , 1998, Neural Computation.

[27]  Xin Yao,et al.  Evolving artificial neural networks , 1999, Proc. IEEE.

[28]  S. Baluja,et al.  Using Optimal Dependency-Trees for Combinatorial Optimization: Learning the Structure of the Search Space , 1997 .

[29]  Hans-Georg Beyer,et al.  The Theory of Evolution Strategies , 2001, Natural Computing Series.

[30]  Marc Toussaint,et al.  Neutrality: a necessity for self-adaptation , 2002, Proceedings of the 2002 Congress on Evolutionary Computation. CEC'02 (Cat. No.02TH8600).

[31]  Marc Toussaint,et al.  The Structure of Evolutionary Exploration: On Crossover, Buildings Blocks, and Estimation-Of-Distribution Algorithms , 2002, GECCO.

[32]  Thomas Bäck,et al.  Evolutionary Algorithms in Theory and Practice , 1996 .

[33]  Simon M. Lucas,et al.  Growing adaptive neural networks with graph grammars , 1995, ESANN.

[34]  M. Conrad The geometry of evolution. , 1990, Bio Systems.

[35]  Christopher R. Stephens,et al.  Effective Fitness as an Alternative Paradigm for Evolutionary Computation I: General Formalism , 2000, Genetic Programming and Evolvable Machines.

[36]  Steven J. Nowlan,et al.  Mixtures of Controllers for Jump Linear and Non-Linear Plants , 1993, NIPS.

[37]  R. Jacobs Computational studies of the development of functionally specialized neural modules , 1999, Trends in Cognitive Sciences.

[38]  Richard S. Sutton,et al.  Reinforcement Learning , 1992, Handbook of Machine Learning.

[39]  Marc Toussaint,et al.  On Classes of Functions for which No Free Lunch Results Hold , 2001, Inf. Process. Lett..

[40]  Vladimir N. Vapnik,et al.  The Nature of Statistical Learning Theory , 2000, Statistics for Engineering and Information Science.

[41]  David H. Wolpert,et al.  No free lunch theorems for optimization , 1997, IEEE Trans. Evol. Comput..

[42]  A G Barto,et al.  Learning by statistical cooperation of self-interested neuron-like computing elements. , 1985, Human neurobiology.

[43]  A. Wagner DOES EVOLUTIONARY PLASTICITY EVOLVE? , 1996, Evolution; international journal of organic evolution.

[44]  H. Waelbroeck,et al.  Codon Bias and Mutability in HIV Sequences , 1997, Journal of Molecular Evolution.

[45]  Shumeet Baluja,et al.  A Method for Integrating Genetic Search Based Function Optimization and Competitive Learning , 1994 .

[46]  Marc Toussaint,et al.  On the Evolution of Phenotypic Exploration Distributions , 2002, FOGA.

[47]  Hans-Paul Schwefel,et al.  Evolution and optimum seeking , 1995, Sixth-generation computer technology series.

[48]  P. Schuster,et al.  IR-98-039 / April Continuity in Evolution : On the Nature of Transitions , 1998 .

[49]  D. Wolpert,et al.  No Free Lunch Theorems for Search , 1995 .

[50]  Frédéric Gruau,et al.  Automatic Definition of Modular Neural Networks , 1994, Adapt. Behav..

[51]  David E. Goldberg,et al.  Linkage Problem, Distribution Estimation, and Bayesian Networks , 2000, Evolutionary Computation.

[52]  M. Kimura,et al.  DNA and the neutral theory. , 1986, Philosophical transactions of the Royal Society of London. Series B, Biological sciences.

[53]  Marc Toussaint,et al.  Task-dependent evolution of modularity in neural networks , 2002 .

[54]  S. Rice THE EVOLUTION OF CANALIZATION AND THE BREAKING OF VON BAER'S LAWS: MODELING THE EVOLUTION OF DEVELOPMENT WITH EPISTASIS , 1998, Evolution; international journal of organic evolution.

[55]  Günter P. Wagner,et al.  Genetic measurement theory of epistatic effects , 2004, Genetica.

[56]  Heinz Mühlenbein,et al.  Schemata, Distributions and Graphical Models in Evolutionary Optimization , 1999, J. Heuristics.

[57]  R. Riedl A Systems-Analytical Approach to Macro-Evolutionary Phenomena , 1977, The Quarterly Review of Biology.

[58]  A. A. Zhigli︠a︡vskiĭ,et al.  Theory of Global Random Search , 1991 .

[59]  David E. Goldberg,et al.  A Survey of Optimization by Building and Using Probabilistic Models , 2002, Comput. Optim. Appl..

[60]  Lee Altenberg,et al.  Genome Growth and the Evolution of the Genotype-Phenotype Map , 1995, Evolution and Biocomputation.

[61]  Michael I. Jordan,et al.  Task Decomposition Through Competition in a Modular Connectionist Architecture: The What and Where Vision Tasks , 1990, Cogn. Sci..

[62]  Marc Toussaint,et al.  A neural model for multi-expert architectures , 2002, Proceedings of the 2002 International Joint Conference on Neural Networks. IJCNN'02 (Cat. No.02CH37290).

[63]  Gregory S. Hornby,et al.  The advantages of generative grammatical encodings for physical design , 2001, Proceedings of the 2001 Congress on Evolutionary Computation (IEEE Cat. No.01TH8546).

[64]  J. Rissanen,et al.  Modeling By Shortest Data Description* , 1978, Autom..

[65]  Thomas Bäck,et al.  An Overview of Parameter Control Methods by Self-Adaption in Evolutionary Algorithms , 1998, Fundam. Informaticae.

[66]  Anjen Chenn,et al.  Regulation of Cerebral Cortical Size by Control of Cell Cycle Exit in Neural Precursors , 2002, Science.

[67]  G. Wagner,et al.  Modeling genetic architecture: a multilinear theory of gene interaction. , 2001, Theoretical population biology.

[68]  P. Schuster Landscapes and molecular evolution , 1997 .

[69]  P. Callaerts,et al.  Induction of ectopic eyes by targeted expression of the eyeless gene in Drosophila. , 1995, Science.

[70]  Dale Schuurmans A New Metric-Based Approach to Model Selection , 1997, AAAI/IAAI.

[71]  Jonathan L. Shapiro,et al.  The Sensitivity of PBIL to Its Learning Rate, and How Detailed Balance Can Remove It , 2002, FOGA.

[72]  Nikolaus Hansen,et al.  Completely Derandomized Self-Adaptation in Evolution Strategies , 2001, Evolutionary Computation.

[73]  Kurt Hornik,et al.  Multilayer feedforward networks are universal approximators , 1989, Neural Networks.

[74]  Marc Toussaint,et al.  On model selection and the disability of neural networks to decompose tasks , 2002, Proceedings of the 2002 International Joint Conference on Neural Networks. IJCNN'02 (Cat. No.02CH37290).