Evolutionary Computation for Reinforcement Learning
暂无分享,去创建一个
[1] Alexander Zelinsky,et al. Q-Learning in Continuous State and Action Spaces , 1999, Australian Joint Conference on Artificial Intelligence.
[2] Stewart W. Wilson. Function approximation with a classifier system , 2001 .
[3] Peter Nordin,et al. An On-Line Method to Evolve Behavior and to Control a Miniature Robot in Real Time with Genetic Programming , 1996, Adapt. Behav..
[4] Richard K. Belew,et al. New Methods for Competitive Coevolution , 1997, Evolutionary Computation.
[5] Shimon Whiteson,et al. Critical factors in the empirical performance of temporal difference and evolutionary methods for reinforcement learning , 2010, Autonomous Agents and Multi-Agent Systems.
[6] Samir W. Mahfoud. A Comparison of Parallel and Sequential Niching Methods , 1995, ICGA.
[7] MSc PhD Tim Kovacs BA. Strength or Accuracy: Credit Assignment in Learning Classifier Systems , 2004, Distinguished Dissertations.
[8] Ida G. Sprinkhuizen-Kuyper,et al. Evolving Artificial Neural Networks using the "Baldwin Effect" † , 1995 .
[9] Ida G. Sprinkhuizen-Kuyper,et al. Evolving Neural Networks Using the "Baldwin Effect" , 1995, ICANNGA.
[10] Simon Haykin,et al. Neural Networks: A Comprehensive Foundation , 1998 .
[11] L. Darrell Whitley,et al. Genetic Reinforcement Learning for Neurocontrol Problems , 2004, Machine Learning.
[12] Diego Calvanese,et al. Unifying Class-Based Representation Formalisms , 2011, J. Artif. Intell. Res..
[13] Leslie Pack Kaelbling,et al. Learning in embedded systems , 1993 .
[14] A. P. Wieland,et al. Evolving neural network controllers for unstable systems , 1991, IJCNN-91-Seattle International Joint Conference on Neural Networks.
[15] Ben Tse,et al. Autonomous Inverted Helicopter Flight via Reinforcement Learning , 2004, ISER.
[16] J. Krebs,et al. Arms races between and within species , 1979, Proceedings of the Royal Society of London. Series B. Biological Sciences.
[17] D. E. Goldberg,et al. Genetic Algorithms in Search , 1989 .
[18] Risto Miikkulainen,et al. Competitive Coevolution through Evolutionary Complexification , 2011, J. Artif. Intell. Res..
[19] R. French,et al. Genes, Phenes and the Baldwin Effect: Learning and Evolution in a Simulated Population , 1994 .
[20] Richard S. Sutton,et al. Reinforcement Learning: An Introduction , 1998, IEEE Trans. Neural Networks.
[21] Risto Miikkulainen,et al. Culling and Teaching in Neuro-Evolution , 1997, ICGA.
[22] Kenneth O. Stanley,et al. A Hypercube-Based Encoding for Evolving Large-Scale Neural Networks , 2009, Artificial Life.
[23] David E. Goldberg,et al. Genetic Algorithms with Sharing for Multimodalfunction Optimization , 1987, ICGA.
[24] D. R. McGregor,et al. Designing application-specific neural networks using the structured genetic algorithm , 1992, [Proceedings] COGANN-92: International Workshop on Combinations of Genetic Algorithms and Neural Networks.
[25] Asunción Gómez-Pérez,et al. The Semantic Web: Research and Applications, Second European Semantic Web Conference, ESWC 2005, Heraklion, Crete, Greece, May 29 - June 1, 2005, Proceedings , 2005, ESWC.
[26] Jürgen Schmidhuber,et al. Evolving Modular Fast-Weight Networks for Control , 2005, ICANN.
[27] Shimon Whiteson,et al. Comparing evolutionary and temporal difference methods in a reinforcement learning domain , 2006, GECCO.
[28] Kalyanmoy Deb,et al. A Comparative Analysis of Selection Schemes Used in Genetic Algorithms , 1990, FOGA.
[29] Geoffrey E. Hinton,et al. How Learning Can Guide Evolution , 1996, Complex Syst..
[30] Peter M. Todd,et al. Parental Guidance Suggested: How Parental Imprinting Evolves Through Sexual Selection as an Adaptive Learning Mechanism , 1993, Adapt. Behav..
[31] Joel Lehman,et al. Evolving policy geometry for scalable multiagent learning , 2010, AAMAS.
[32] Stefan Schaal,et al. Natural Actor-Critic , 2003, Neurocomputing.
[33] Sridhar Mahadevan,et al. Proto-value Functions: A Laplacian Framework for Learning Representation and Control in Markov Decision Processes , 2007, J. Mach. Learn. Res..
[34] J. A. Lozano,et al. Estimation of Distribution Algorithms: A New Tool for Evolutionary Computation , 2001 .
[35] R. K. Ursem. Multi-objective Optimization using Evolutionary Algorithms , 2009 .
[36] Christophe G. Giraud-Carrier,et al. Unifying Learning with Evolution Through Baldwinian Evolution and Lamarckism , 2000, Advances in Computational Intelligence and Learning.
[37] Sean Luke,et al. Cooperative Multi-Agent Learning: The State of the Art , 2005, Autonomous Agents and Multi-Agent Systems.
[38] Takaya Arita,et al. Interactions between learning and evolution: the outstanding strategy generated by the Baldwin effect. , 2004, Bio Systems.
[39] John J. Grefenstette,et al. Evolutionary Algorithms for Reinforcement Learning , 1999, J. Artif. Intell. Res..
[40] Risto Miikkulainen,et al. Coevolution of Role-Based Cooperation in Multiagent Systems , 2009, IEEE Transactions on Autonomous Mental Development.
[41] Risto Miikkulainen,et al. Evolving Soccer Keepaway Players Through Task Decomposition , 2005, Machine Learning.
[42] Francesco Mondada,et al. Evolution of homing navigation in a real mobile robot , 1996, IEEE Trans. Syst. Man Cybern. Part B.
[43] David E. Goldberg,et al. Genetic Algorithms in Search Optimization and Machine Learning , 1988 .
[44] Stewart W. Wilson. Classifier Fitness Based on Accuracy , 1995, Evolutionary Computation.
[45] Gerald Tesauro. Comments on “Co-Evolution in the Successful Learning of Backgammon Strategy” , 2004, Machine Learning.
[46] Risto Miikkulainen,et al. Forming Neural Networks Through Efficient and Adaptive Coevolution , 1997, Evolutionary Computation.
[47] Edwin D. de Jong,et al. The Incremental Pareto-Coevolution Archive , 2004, GECCO.
[48] Thomas Jansen,et al. The Cooperative Coevolutionary (11) EA , 2004, Evolutionary Computation.
[49] Keith L. Downing,et al. Reinforced Genetic Programming , 2001, Genetic Programming and Evolvable Machines.
[50] Richard S. Sutton,et al. Integrated Architectures for Learning, Planning, and Reacting Based on Approximating Dynamic Programming , 1990, ML.
[51] Luc Steels,et al. Emergent functionality in robotic agents through on-line evolution , 1994 .
[52] Dirk P. Kroese,et al. The Cross-Entropy Method: A Unified Approach to Combinatorial Optimization, Monte-Carlo Simulation and Machine Learning , 2004 .
[53] Grzegorz Rozenberg,et al. Handbook of Natural Computing , 2011, Springer Berlin Heidelberg.
[54] Verena Heidrich-Meisner,et al. Neuroevolution strategies for episodic reinforcement learning , 2009, J. Algorithms.
[55] Olivier Sigaud,et al. YACS: a new learning classifier system using anticipation , 2002, Soft Comput..
[56] A. Lindenmayer. Mathematical models for cellular interactions in development. II. Simple and branching filaments with two-sided inputs. , 1968, Journal of theoretical biology.
[57] Risto Miikkulainen,et al. Evolving a Roving Eye for Go , 2004, GECCO.
[58] Moshe Sipper,et al. Evolving artificial neural networks with FINCH , 2013, GECCO '13 Companion.
[59] Martin V. Butz,et al. Sequential problems that test generalization in learning classifier systems , 2009, Evol. Intell..
[60] Simon M. Lucas,et al. Temporal Difference Learning Versus Co-Evolution for Acquiring Othello Position Evaluation , 2006, 2006 IEEE Symposium on Computational Intelligence and Games.
[61] Christian Igel,et al. Variable Metric Reinforcement Learning Methods Applied to the Noisy Mountain Car Problem , 2008, EWRL.
[62] Leslie Pack Kaelbling,et al. On the Complexity of Solving Markov Decision Problems , 1995, UAI.
[63] W. Daniel Hillis,et al. Co-evolving parasites improve simulated evolution as an optimization procedure , 1990 .
[64] Kagan Tumer,et al. Optimal Payoff Functions for Members of Collectives , 2001, Adv. Complex Syst..
[65] Dario Floreano,et al. Evolution of Plastic Control Networks , 2001, Auton. Robots.
[66] Christian Igel,et al. Uncertainty handling CMA-ES for reinforcement learning , 2009, GECCO.
[67] Byoung-Tak Zhang,et al. Evolving Optimal Neural Networks Using Genetic Algorithms with Occam's Razor , 1993, Complex Syst..
[68] Jürgen Schmidhuber,et al. Co-evolving recurrent neurons learn deep memory POMDPs , 2005, GECCO '05.
[69] Daniele Loiacono,et al. On-line neuroevolution applied to The Open Racing Car Simulator , 2009, 2009 IEEE Congress on Evolutionary Computation.
[70] Christian Igel,et al. Neuroevolution for reinforcement learning using evolution strategies , 2003, The 2003 Congress on Evolutionary Computation, 2003. CEC '03..
[71] Jordan B. Pollack,et al. Pareto Optimality in Coevolutionary Learning , 2001, ECAL.
[72] Jordan B. Pollack,et al. A Game-Theoretic Approach to the Simple Coevolutionary Algorithm , 2000, PPSN.
[73] Risto Miikkulainen,et al. Accelerated Neural Evolution through Cooperatively Coevolved Synapses , 2008, J. Mach. Learn. Res..
[74] Peter J. Fleming,et al. On-line evolution of robust control systems: an industrial active magnetic bearing application , 2001 .
[75] David B. Fogel,et al. Evolving an expert checkers playing program without using human expertise , 2001, IEEE Trans. Evol. Comput..
[76] Sean Luke,et al. Archive-based cooperative coevolutionary algorithms , 2006, GECCO '06.
[77] Xin Yao,et al. Evolving artificial neural networks , 1999, Proc. IEEE.
[78] Kenneth A. De Jong,et al. Using genetic algorithms for concept learning , 1993, Machine Learning.
[79] Daniele Loiacono,et al. Learning to Drive in the Open Racing Car Simulator Using Online Neuroevolution , 2010, IEEE Transactions on Computational Intelligence and AI in Games.
[80] Arthur Tay,et al. Online adaptive controller for simulated car racing , 2008, 2008 IEEE Congress on Evolutionary Computation (IEEE World Congress on Computational Intelligence).
[81] Kagan Tumer,et al. Efficient Evaluation Functions for Evolving Coordination , 2008, Evolutionary Computation.
[82] David H. Ackley,et al. Interactions between learning and evolution , 1991 .
[83] Risto Miikkulainen,et al. Evolving Keepaway Soccer Players through Task Decomposition , 2003, GECCO.
[84] Riccardo Poli,et al. Genetic and Evolutionary Computation – GECCO 2004 , 2004, Lecture Notes in Computer Science.
[85] Erkki Oja,et al. Artificial Neural Networks: Formal Models and Their Applications - ICANN 2005, 15th International Conference, Warsaw, Poland, September 11-15, 2005, Proceedings, Part II , 2005, International Conference on Artificial Neural Networks.
[86] M.A. Wiering,et al. Reinforcement Learning in Continuous Action Spaces , 2007, 2007 IEEE International Symposium on Approximate Dynamic Programming and Reinforcement Learning.
[87] Stefano Nolfi,et al. Learning to Adapt to Changing Environments in Evolving Neural Networks , 1996, Adapt. Behav..
[88] Jordan B. Pollack,et al. Creating High-Level Components with a Generative Representation for Body-Brain Evolution , 2002, Artificial Life.
[89] Simon M. Lucas,et al. Coevolution versus self-play temporal difference learning for acquiring position evaluation in small-board go , 2005, IEEE Transactions on Evolutionary Computation.
[90] J. Neumann. Zur Theorie der Gesellschaftsspiele , 1928 .
[91] Aristid Lindenmayer,et al. Mathematical Models for Cellular Interactions in Development , 1968 .
[92] J. Baldwin. A New Factor in Evolution , 1896, The American Naturalist.
[93] Dario Floreano,et al. Evolving Vision-Based Flying Robots , 2002, Biologically Motivated Computer Vision.
[94] John H. Holland,et al. Cognitive systems based on adaptive algorithms , 1977, SGAR.
[95] Risto Miikkulainen,et al. Active Guidance for a Finless Rocket Using Neuroevolution , 2003, GECCO.
[96] Kenneth O. Stanley,et al. Autonomous Evolution of Topographic Regularities in Artificial Neural Networks , 2010, Neural Computation.
[97] Goldberg,et al. Genetic algorithms , 1993, Robust Control Systems with Genetic Algorithms.
[98] Martin V. Butz,et al. Anticipatory Learning Classifier Systems and Factored Reinforcement Learning , 2009, ABiALS.
[99] Kenneth A. De Jong,et al. An Analysis of the Interacting Roles of Population Size and Crossover in Genetic Algorithms , 1990, PPSN.
[100] L. Darrell Whitley,et al. Lamarckian Evolution, The Baldwin Effect and Function Optimization , 1994, PPSN.
[101] Inman Harvey,et al. Evolutionary Robotics: A Survey of Applications and Problems , 1998, EvoRobot.
[102] Risto Miikkulainen,et al. Evolving neural networks for strategic decision-making problems , 2009, Neural Networks.
[103] Seong-Whan Lee,et al. Biologically Motivated Computer Vision , 2002, Lecture Notes in Computer Science.
[104] R. Paul Wiegand,et al. An empirical analysis of collaboration methods in cooperative coevolutionary algorithms , 2001 .
[105] Shimon Whiteson,et al. On-line evolutionary computation for reinforcement learning in stochastic domains , 2006, GECCO.
[106] Neil D. Lawrence,et al. Missing Data in Kernel PCA , 2006, ECML.
[107] Risto Miikkulainen,et al. Coevolution of neural networks using a layered pareto archive , 2006, GECCO.
[108] José del R. Millán,et al. Continuous-Action Q-Learning , 2002, Machine Learning.
[109] Martin V. Butz,et al. Learning sensorimotor control structures with XCSF: redundancy exploitation and dynamic control , 2009, GECCO '09.
[110] Frédéric Gruau,et al. Automatic Definition of Modular Neural Networks , 1994, Adapt. Behav..
[111] Petros Koumoutsakos,et al. Reducing the Time Complexity of the Derandomized Evolution Strategy with Covariance Matrix Adaptation (CMA-ES) , 2003, Evolutionary Computation.
[112] L. Buşoniu. Evolutionary function approximation for reinforcement learning , 2006 .
[113] Jürgen Schmidhuber,et al. Training Recurrent Networks by Evolino , 2007, Neural Computation.
[114] Kenneth O. Stanley,et al. Evolving Static Representations for Task Transfer , 2010, J. Mach. Learn. Res..
[115] Nicholas J. Radcliffe,et al. Genetic set recombination and its application to neural network topology optimisation , 1993, Neural Computing & Applications.
[116] Serge Kernbach,et al. Evolutionary robotics: The next-generation-platform for on-line and on-board artificial evolution , 2009, 2009 IEEE Congress on Evolutionary Computation.
[117] Tim Kovacs,et al. Foundations of learning classifier systems: An introduction , 2005 .
[118] Zixing Cai,et al. Cooperative Coevolutionary Adaptive Genetic Algorithm in Path Planning of Cooperative Multi-Mobile Robot Systems , 2002, J. Intell. Robotic Syst..
[119] Jordan B. Pollack,et al. Co-Evolution in the Successful Learning of Backgammon Strategy , 1998, Machine Learning.
[120] Jeffrey L. Elman,et al. Learning and Evolution in Neural Networks , 1994, Adapt. Behav..
[121] Kenneth O. Stanley. A Hypercube-Based Indirect Encoding for Evolving Large-Scale Neural Networks , 2009 .
[122] Kenneth O. Stanley,et al. A Case Study on the Critical Role of Geometric Regularity in Machine Learning , 2008, AAAI.
[123] Martin V. Butz,et al. Function Approximation With XCS: Hyperellipsoidal Conditions, Recursive Least Squares, and Compaction , 2008, IEEE Transactions on Evolutionary Computation.
[124] Kenneth A. De Jong,et al. Cooperative Coevolution: An Architecture for Evolving Coadapted Subcomponents , 2000, Evolutionary Computation.
[125] Gilbert Syswerda,et al. Uniform Crossover in Genetic Algorithms , 1989, ICGA.
[126] Risto Miikkulainen,et al. Solving Non-Markovian Control Tasks with Neuro-Evolution , 1999, IJCAI.
[127] Gerald Tesauro,et al. TD-Gammon, a Self-Teaching Backgammon Program, Achieves Master-Level Play , 1994, Neural Computation.
[128] Shimon Whiteson,et al. Neuroevolutionary reinforcement learning for generalized helicopter control , 2009, GECCO.
[129] Risto Miikkulainen,et al. A Taxonomy for Artificial Embryogeny , 2003, Artificial Life.
[130] Martin V. Butz,et al. Anticipatory Learning Classifier Systems , 2002, Genetic Algorithms and Evolutionary Computation.
[131] Dilip Kumar Pratihar,et al. Evolutionary robotics—A review , 2003 .
[132] Edwin D de Jong. A monotonic archive for pareto-coevolution. , 2007, Evolutionary computation.
[133] Kenji Doya,et al. Reinforcement Learning in Continuous Time and Space , 2000, Neural Computation.
[134] Jan Drugowitsch. Design and Analysis of Learning Classifier Systems - A Probabilistic Approach , 2008, Studies in Computational Intelligence.
[135] Lihong Li,et al. Analyzing feature generation for value-function approximation , 2007, ICML '07.
[136] Larry Bull,et al. Accuracy-based Neuro And Neuro-fuzzy Classifier Systems , 2002, GECCO.
[137] Pedro Larrañaga,et al. Estimation of Distribution Algorithms , 2002, Genetic Algorithms and Evolutionary Computation.
[138] Julian Togelius,et al. Point-to-Point Car Racing: an Initial Study of Evolution Versus Temporal Difference Learning , 2007, 2007 IEEE Symposium on Computational Intelligence and Games.
[139] Gary B. Lamont,et al. Evolutionary Algorithms for Solving Multi-Objective Problems , 2002, Genetic Algorithms and Evolutionary Computation.
[140] Martin V. Butz,et al. Context-dependent predictions and cognitive arm control with XCSF , 2008, GECCO '08.
[141] Shimon Whiteson,et al. The Reinforcement Learning Competitions , 2010 .
[142] Olivier Sigaud,et al. Combining latent learning with dynamic programming in the modular anticipatory classifier system , 2005, Eur. J. Oper. Res..
[143] Xin Yao,et al. Automatic modularization by speciation , 1996, Proceedings of IEEE International Conference on Evolutionary Computation.
[144] Martin V. Butz,et al. Gradient descent methods in learning classifier systems: improving XCS performance in multistep problems , 2005, IEEE Transactions on Evolutionary Computation.
[145] Francisco B. Pereira,et al. Understanding the role of learning in the evolution of busy beavers: a comparison between the baldwin effect and a Lamarckian strategy , 2001 .
[146] Jürgen Schmidhuber,et al. Evolino: Hybrid Neuroevolution/Optimal Linear Search for Sequence Learning , 2005, IJCAI.
[147] L. Darrell Whitley,et al. Adding Learning to the Cellular Development of Neural Networks: Evolution and the Baldwin Effect , 1993, Evolutionary Computation.
[148] John H. Holland,et al. Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence , 1992 .
[149] Risto Miikkulainen,et al. Evolving neural networks for fractured domains , 2008, GECCO '08.
[150] Risto Miikkulainen,et al. Efficient Non-linear Control Through Neuroevolution , 2006, ECML.
[151] Risto Miikkulainen,et al. Evolving adaptive neural networks with and without adaptive synapses , 2003, The 2003 Congress on Evolutionary Computation, 2003. CEC '03..
[152] Mitchell A. Potter,et al. EVOLVING NEURAL NETWORKS WITH COLLABORATIVE SPECIES , 2006 .
[153] Andrea Bonarini,et al. An Introduction to Learning Fuzzy Classifier Systems , 1999, Learning Classifier Systems.
[154] Martin V. Butz,et al. Rule-Based Evolutionary Online Learning Systems - A Principled Approach to LCS Analysis and Design , 2006, Studies in Fuzziness and Soft Computing.
[155] Edwin D. de Jong,et al. Coevolutionary Principles , 2012, Handbook of Natural Computing.
[156] Christian Igel,et al. Hoeffding and Bernstein races for selecting policies in evolutionary direct policy search , 2009, ICML '09.
[157] Marco Colombetti,et al. Robot Shaping: An Experiment in Behavior Engineering , 1997 .
[158] Steffen Priesterjahn,et al. Real-time imitation-based adaptation of gaming behaviour in modern computer games , 2008, GECCO '08.
[159] Stefano Nolfi,et al. Evolutionary robotics , 1998, Lecture Notes in Computer Science.
[160] Risto Miikkulainen,et al. Evolving Neural Networks through Augmenting Topologies , 2002, Evolutionary Computation.
[161] Risto Miikkulainen,et al. Efficient Reinforcement Learning through Symbiotic Evolution , 2004 .