Neural Networks
Our research concentrates on understanding and generating intelligent behavior with artificial neural networks. On one hand, the goal is to better understand human information processing, that is, how intelligent behavior in humans arises from neural network mechanisms. On the other, the research aims at building more intelligent artificial systems. Our approach is to develop algorithms and architectures that explicitly represent and make use of the structure in the task, such as schemas, subgoals, and modularity. This way it is possible to build neural network models of more complex behavior than is possible with traditional uniform network architectures. For example, high-level processes such as schema learning, sentence understanding, and game playing can be implemented with modular neural networks, and such systems can often be more efficient and cognitively valid than traditional models.
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Nora E. Aguirre-Celis Ph.D. Student naguirre [at] cs utexas edu
Erkin Bahceci Ph.D. Student erkin [at] cs utexas edu
Julian Bishop Ph.D. Student julian [at] cs utexas edu
Igor V. Karpov Ph.D. Student ikarpov [at] gmail com
Joel Lehman Postdoctoral Fellow joel [at] cs utexas edu
Dan Lessin Ph.D. Student dlessin [at] cs utexas edu
Xun Li Ph.D. Student xun bhsfer [at] cs utexas edu
Risto Miikkulainen Faculty risto [at] cs utexas edu
Padmini Rajagopalan Ph.D. Student padmini [at] cs utexas edu
Aditya Rawal Ph.D. Student aditya [at] cs utexas edu
Jeremy Stober Ph.D. Student stober [at] cs utexas edu
Wesley Tansey Ph.D. Student tansey [at] cs utexas edu
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Adapting Morphology to Multiple Tasks in Evolved Virtual Creatures 2014
Dan Lessin, Don Fussell, Risto Miikkulainen, To Appear In Proceedings of The Fourteenth International Conference on the Synthesis and Simulation of Living Systems (ALIFE 14) 2014 2014.
Evolution of Communication in Mate Selection 2014
Aditya Rawal, Janette Boughman and Risto Miikkulainen, To Appear In Proceedings of The Fourteenth International Conference on the Synthesis and Simulation of Living Systems (ALIFE 14) , New York, USA, July, 2014 2014.
Evolving Multimodal Behavior Through Modular Multiobjective Neuroevolution 2014
Jacob Schrum, PhD Thesis, The University of Texas at Austin. Tech Report TR-14-07.
Evolving Multimodal Behavior Through Subtask and Switch Neural Networks 2014
Xun Li, Risto Miikkulainen, Proceedings of The Fourteenth International Conference on the Synthesis and Simulation of Living Systems (ALIFE 14) (2014).
Evolving Multimodal Behavior With Modular Neural Networks in Ms. Pac-Man 2014
Jacob Schrum and Risto Miikkulainen, In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2014), pp. 325--332, Vancouver, BC, Canada, July 2014. Best Paper: Digital Entertainment and Arts.
General Intelligence through Prolonged Evolution of Densely Connected Neural Networks 2014
Padmini Rajagopalan, Aditya Rawal, Kay E. Holekamp and Risto Miikkulainen, To Appear In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2014), Vancouver, BC, Canada, July 2014.
GRADE: Machine Learning Support for Graduate Admissions 2014
Austin Waters, Risto Miikkulainen, To Appear In AI Magazine (2014).
Infinite-Word Topic Models for Digital Media 2014
Austin Waters, PhD Thesis, Department of Computer Science, The University of Texas at Austin.
Overcoming Deception in Evolution of Cognitive Behaviors 2014
Joel Lehman and Risto Miikkulainen, To Appear In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2014), Vancouver, BC, Canada, July 2014.
The Evolution of General Intelligence 2014
Padmini Rajagopalan, Kay E. Holekamp and Risto Miikkulainen, To Appear In Proceedings of The Fourteenth International Conference on the Synthesis and Simulation of Living Systems (ALIFE 14), New York, NY 2014.
Trading Control Intelligence for Physical Intelligence: Muscle Drives in Evolved Virtual Creatures 2014
Dan Lessin, Don Fussell, Risto Miikkulainen, To Appear In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO) 2014 2014.
A Computational Account of Bilingual Aphasia Rehabilitation 2013
Swathi Kiran, Uli Grasemann, Chaleece Sandberg, and Risto Miikkulainen, Bilingualism: Language and Cognition, Vol. 16 (2013), pp. 325-342.
A Measure-Theoretic Analysis of Stochastic Optimization 2013
Alan J. Lockett and Risto Miikkulainen, In Proceedings of the 12th International Workshop on Foundations of Genetic Algorithms (FOGA-2013) 2013. ACM Press.
A Neuroevolution Approach to General Atari Game Playing 2013
Matthew Hausknecht, Joel Lehman, Risto Miikkulainen, and Peter Stone, In IEEE Transactions on Computational Intelligence and AI in Games 2013.
Architecture of a Cyberphysical Avatar 2013
Song Han, Aloysius K. Mok, Jianyong Meng, Yi-Hung Wei, Pei-Chi Huang, Quan Leng, Xiuming Zhu, Luis Sentis, Kwan Suk Kim, and Risto Miikkulainen, In Proceedings of the ACM/IEEE Fourth International Conference on Cyber-Physical Systems (ICCPS-2013) 2013.
Boosting Interactive Evolution using Human Computation Markets 2013
Joel Lehman and Risto Miikkulainen, To Appear In Proceedings of the 2nd International Conference on the Theory and Practice of Natural Computation, pp. 18 pages 2013. Springer.
Effective Diversity Maintenance in Deceptive Domains 2013
Joel Lehman, Kenneth O. Stanley and Risto Miikkulainen, To Appear In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO) 2013 2013.
Evolutionary Annealing: Global Optimization in Arbitrary Measure Spaces 2013
Alan J Lockett and Risto Miikkulainen, Journal of Global Optimization (2013), pp. 1--34.
Extended Scaled Neural Predictor for Improved Branch Prediction 2013
Zihao Zhou, Mayank Kejriwal and Risto Miikkulainen, In Proceedings of the International Joint Conference on Neural Networks 2013. IEEE.
GRADE: Machine Learning Support for Graduate Admissions 2013
Austin Waters, Risto Miikkulainen, In Proceedings of the 25th Conference on Innovative Applications of Artificial Intelligence 2013.
IJCNN-2013 Tutorial on Evolution of Neural Networks 2013
Risto Miikkulainen, To Appear In unpublished. Tutorial slides..
MARLEDA: Effective Distribution Estimation through Markov Random Fields 2013
Matthew Alden and Risto Miikkulainen, Technical Report TR-13-18, Department of Computer Science, The University of Texas at Austin.
Measure-Theoretic Analysis of Performance in Evolutionary Algorithms 2013
Alan J Lockett, In Proceedings of the 2013 IEEE Congress on Evolutionary Computation (CEC-2013) 2013. IEEE Press.
Neuroannealing: Martingale-Driven Optimization for Neural Networks 2013
Alan J Lockett and Risto Miikkulainen, In Proceedings of the 2013 Genetic and Evolutionary Computation Conference (GECCO-2013) 2013. ACM Press.
Neuroevolution 2013
Joel Lehman and Risto Miikkulainen, Scholarpedia, Vol. 8, 6 (2013), pp. 30977.
Open-Ended Behavioral Complexity for Evolved Virtual Creatures 2013
Dan Lessin, Don Fussell, Risto Miikkulainen, In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO) 2013 2013.
Using Both Latent and Supervised Shared Topics for Multitask Learning 2013
Ayan Acharya, Aditya Rawal, Raymond J. Mooney, Eduardo R. Hruschka, In European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML/PKDD), pp. 369--384, Prague, Czech Republic, September 2013.
Using Symmetry and Evolutionary Search to Minimize Sorting Networks 2013
Vinod K. Valsalam and Risto Miikkulainen, Journal of Machine Learning Research, Vol. 14, Feb (2013), pp. 303--331.
A Probabilistic Architecture for Algorithm Portfolios 2012
Bryan Silverthorn, PhD Thesis, Department of Computer Science, The University of Texas at Austin.
Accelerating Evolution via Egalitarian Social Learning 2012
Wesley Tansey, Eliana Feasley, and Risto Miikkulainen, Proceedings of the 14th Annual Genetic and Evolutionary Computation Conference (GECCO 2012) (2012).
Architecture of a Cyberphysical Avatar 2012
Song Han, Aloysius K. Mok, Jianyong Meng, Yi-Hung Wei, Pei-Chi Huang, Xiuming Zhu, Luis Sentis, Kan Suk Kim, Risto Miikkulainen, and Jacob Menashe, In Proceedings of the International Workshop on Real-Time and Distributed Computing in Emerging Applications (REACTION) 2012.
Believable Bot Navigation via Playback of Human Traces 2012
Igor V. Karpov, Jacob Schrum, Risto Miikkulainen, In Believable Bots, Philip F. Hingston (Eds.), pp. 151--170 2012. Springer Berlin Heidelberg.
Constructing Controllers for Physical Multilegged Robots using the ENSO Neuroevolution Approach 2012
Vinod K. Valsalam, Jonathan Hiller, Robert MacCurdy, Hod Lipson and Risto Miikkulainen, Evolutionary Intelligence, Vol. 5, 1 (2012), pp. 1--12.
Evaluating Modular Neuroevolution in Robotic Keepaway Soccer 2012
Anand Subramoney, Masters Thesis, Department of Computer Science, The University of Texas at Austin. 54 pages.
Evaluation Methods for Active Human-Guided Neuroevolution in Games 2012
Igor Karpov, Leif Johnson, Vinod Valsalam and Risto Miikkulainen, In 2012 AAAI Fall Symposium on Robots Learning Interactively from Human Teachers (RLIHT), November 2012.
Evolution of a Communication Code in Cooperative Tasks 2012
Aditya Rawal, Padmini Rajagopalan, Risto Miikkulainen and Kay Holekamp, In Artificial Life (13th International Conference on the Synthesis and Simulation of Living Systems), East Lansing, Michigan, USA 2012.
Evolving Multimodal Networks for Multitask Games 2012
Jacob Schrum and Risto Miikkulainen, IEEE Transactions on Computational Intelligence and AI in Games, Vol. 4, 2 (2012), pp. 94--111. IEEE.
General-Purpose Optimization Through Information-Maximization 2012
Alan J Lockett, PhD Thesis, Department of Computer Sciences, The University of Texas at Austin. Tech Report AI12-11.
Humanlike Combat Behavior via Multiobjective Neuroevolution 2012
Jacob Schrum, Igor V. Karpov and Risto Miikkulainen, In Believable Bots, Philip F. Hingston (Eds.), pp. 119--150 2012. Springer Berlin Heidelberg.
HyperNEAT-GGP: A HyperNEAT-based Atari General Game Player 2012
Matthew Hausknecht, Piyush Khandelwal, Risto Miikkulainen, Peter Stone, In Genetic and Evolutionary Computation Conference (GECCO) 2012 2012.
Intensive training induces longitudinal changes in meditation state-related EEG oscillatory activity 2012
Manish Saggar, Brandon G King, Anthony P Zanesco, Katherine A MacLean, Stephen R Aichele, Tonya L Jacobs, David A Bridwell, Phillip R Shaver, Erika L Rosenberg, Baljinder K Sahdra, Emilio Ferrer, Akaysha C Tang, George R Mangun, B Alan Wallace, Risto Miikkulainen, and Clifford D Saron, Frontiers in Human NeuroscienceAmishi P Jha (Eds.), Vol. 6, 00256 (2012).
Multiagent Learning through Neuroevolution 2012
Risto Miikkulainen, Eliana Feasley, Leif Johnson, Igor Karpov, Padmini Rajagopalan, Aditya Rawal, and Wesley Tansey, In Advances in Computational Intelligence, J. Liu et al. (Eds.), Vol. LNCS 7311, pp. 24-46, Berlin, Heidelberg: 2012. Springer.
Surviving Solver Sensitivity: An ASP Practitioner's Guide 2012
Bryan Silverthorn, Yuliya Lierler and Marius Schneider, International Conference on Logic Programming (ICLP) (2012).
Task decomposition with neuroevolution in extended predator-prey domain 2012
Ashish Jain, Anand Subramoney, Risto Miikkulainen, In Proceedings of Thirteenth International Conference on the Synthesis and Simulation of Living Systems, East Lansing, MI, USA 2012.
An Integrated Neuroevolutionary Approach to Reactive Control and High-level Strategy 2011
Nate Kohl, Risto Miikkulainen, IEEE Transactions on Evolutionary Computation (2011).
Assisting Machine Learning Through Shaping, Advice and Examples 2011
Igor Karpov, Vinod Valsalam and Risto Miikkulainen, In 2011 IJCAI Workshop on Agents Learning Interactively from Human Teachers (ALIHT), July 2011.
Avoiding Premature Convergence in NeuroEvolution by Broadening the Evolutionary Search 2011
Matthew de Wet, Technical Report HR-11-02, Department of Computer Science, The University of Texas at Austin.
Creating Intelligent Agents through Shaping of Coevolution 2011
Adam Dziuk, Technical Report HR-11-01, Department of Computer Science, The University of Texas at Austin.
Creating Intelligent Agents through Shaping of Coevolution 2011
Adam Dziuk and Risto Miikkulainen, In Proceedings of the Congress on Evolutionary Computation, New Orleans, LA 2011. IEEE.
Evolving Multimodal Networks for Multitask Games 2011
Jacob Schrum and Risto Miikkulainen, In Proceedings of the IEEE Conference on Computational Intelligence and Games (CIG 2011), pp. 102--109, Seoul, South Korea, September 2011. IEEE. (Best Paper Award).
Evolving Symmetry for Modular System Design 2011
Vinod K. Valsalam and Risto Miikkulainen, IEEE Transactions on Evolutionary Computation, Vol. 15, 3 (2011), pp. 368--386.
Human-Assisted Neuroevolution Through Shaping, Advice and Examples 2011
Igor V. Karpov, Vinod K. Valsalam and Risto Miikkulainen, In Proceedings of the 13th Annual Genetic and Evolutionary Computation Conference (GECCO 2011), Dublin, Ireland, July 2011.
Impairment and Rehabilitation in Bilingual Aphasia: A SOM-Based Model 2011
Uli Grasemann, Swathi Kiran, Chaleece Sandberg and Risto Miikkulainen, In Proceedings of WSOM11, 8th Workshop on Self-Organizing Maps, LNCS 6731, J Laaksonen and T. Honkela (Eds.), pp. 207--217, Espoo, Finland 2011. Springer Verlag.
Learning Geometry from Sensorimotor Experience 2011
Jeremy Stober, Risto Miikkulainen, and Benjamin Kuipers, In Proceedings of the First International Conference on Development and Learning and Epigenetic Robotics, Frankfurt am Main, Germany, August 2011.
Learning Polarity from Structure in SAT 2011
Bryan Silverthorn and Risto Miikkulainen, In Theory and Applications of Satisfiability Testing (SAT) 2011. (extended abstract).
Measure-Theoretic Evolutionary Annealing 2011
Alan J. Lockett and Risto Miikkulainen, In Proceedings of the 2011 IEEE Congress on Evolutionary Computation 2011.
Modeling Acute and Compensated Language Disturbance in Schizophrenia 2011
Uli Grasemann, Ralph Hoffman and Risto Miikkulainen, In Proceedings of the 33rd Annual Meeting of the Cognitive Science Society 2011.
Real-Space Evolutionary Annealing 2011
Alan J Lockett and Risto Miikkulainen, In Proceedings of the 2011 Genetic and Evolutionary Computation Conference (GECCO-2011) 2011.
The Role of Reward Structure, Coordination Mechanism and Net Return in the Evolution of Cooperation 2011
Padmini Rajagopalan, Aditya Rawal, Risto Miikkulainen, Marc A. Wiseman and Kay E. Holekamp, In Proceedings of the IEEE Conference on Computational Intelligence and Games (CIG 2011), Seoul, South Korea 2011.
Using Computational Patients to Evaluate Illness Mechanisms in Schizophrenia 2011
Ralph E. Hoffman, Uli Grasemann, Ralitza Gueorguieva, Donald Quinlan, Douglas Lane, and Risto Miikkulainen, Biological Psychiatry, Vol. 69 (2011), pp. 997--1005.
Utilizing Symmetry and Evolutionary Search to Minimize Sorting Networks 2011
Vinod K. Valsalam and Risto Miikkulainen, Technical Report AITR-11-09, Department of Computer Sciences, The University of Texas at Austin.
UT^2: Human-like Behavior via Neuroevolution of Combat Behavior and Replay of Human Traces 2011
Jacob Schrum, Igor V. Karpov and Risto Miikkulainen, In Proceedings of the IEEE Conference on Computational Intelligence and Games (CIG 2011), pp. 329--336, Seoul, South Korea, September 2011. IEEE.
A Computational Model of Language Pathology in Schizophrenia 2010
Uli Grasemann, PhD Thesis, Department of Computer Science, The University of Texas at Austin. 147 pages. Technical report TR-11-11.
An Analysis of Automated Decision Making Methodologies in Role Playing Video Games: Centralized Approach 2010
Christopher Bush, Technical Report HR-10-03, Department of Computer Science, The University of Texas at Austin.
An Analysis of Distributed Decision Making Methodologies in Role Playing Video Games 2010
Matthew Johnston, Technical Report HR-10-09, Department of Computer Science, The University of Texas at Austin.
Behavioral, neuroimaging, and computational evidence for perceptual caching in repetition priming 2010
Manish Saggar, Risto Miikkulainen, David Schnyer, Journal of Brain Research, Vol. 1315 (2010), pp. 75--91.
Coevolution of Role-Based Cooperation in Multi-Agent Systems 2010
Chern Han Yong and Risto Miikkulainen, IEEE Transactions on Autonomous Mental Development, Vol. 1 (2010), pp. 170--186.
Computational models inform clinical science and assessment: An application to category learning in striatal-damaged patients 2010
W. Todd Maddox, J. Vincent Filoteo and Dagmar Zeithamova, Journal of Mathematical Psychology, Vol. 54, 1 (2010), pp. 109-122.
Constructing Competitive and Cooperative Agent Behavior Using Coevolution 2010
Aditya Rawal, Padmini Rajagopalan and Risto Miikkulainen, In IEEE Conference on Computational Intelligence and Games (CIG 2010), Copenhagen, Denmark, August 2010.
Evolving Agent Behavior In Multiobjective Domains Using Fitness-Based Shaping 2010
Jacob Schrum and Risto Miikkulainen, In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2010), pp. 439--446, Portland, Oregon, July 2010.
Hierarchical Neural Networks for Behavior-Based Decision Making 2010
David Robson, Technical Report HR-10-02, Department of Computer Science, The University of Texas at Austin.
Latent Class Models for Algorithm Portfolio Methods 2010
Bryan Silverthorn and Risto Miikkulainen, In Proceedings of the Twenty-Fourth AAAI Conference on Artificial Intelligence 2010.
Neuroevolution 2010
Risto Miikkulainen, In Encyclopedia of Machine Learning, New York 2010. Springer.
Speciation in NEAT 2010
Timothy Nodine, Technical Report HR-10-06, Department of Computer Science, The University of Texas at Austin.
Spherical Topic Models 2010
Joseph Reisinger, Austin Waters, Bryan Silverthorn, and Raymond J. Mooney, In Proceedings of the 27th International Conference on Machine Learning (ICML 2010) 2010.
Utilizing Symmetry in Evolutionary Design 2010
Vinod Valsalam, PhD Thesis, Department of Computer Sciences, The University of Texas at Austin. Technical Report AI-10-04.
A Population Gain Control Model of Spatiotemporal Responses in the Visual Cortex 2009
Yiu Fai Sit, PhD Thesis, Department of Computer Sciences, University of Texas at Austin. Technical Report AI09-06.
Complex Dynamics of V1 Population Responses Explained by a Simple Gain-Control Model 2009
Yiu Fai Sit, Yuzhi Chen, Wilson S. Geisler, Risto Miikkulainen, and Eyal Seidemann, Neuron, Vol. 64 (2009), pp. 943-956.
Computational Predictions on the Receptive Fields and Organization of V2 for Shape Processing 2009
Yiu Fai Sit and Risto Miikkulainen, Neural Computation, Vol. 21, 3 (2009), pp. 762--785.
Evolving Adaptive Intelligence: Using NeuroEvolution with Temporal Difference Methods in the Game Domain 2009
Nathaniel Tucker, Technical Report HR-09-04, Department of Computer Science, The University of Texas at Austin..
Evolving Multi-modal Behavior in NPCs 2009
Jacob Schrum and Risto Miikkulainen, In IEEE Symposium on Computational Intelligence and Games (CIG 2009), pp. 325--332, Milan, Italy, September 2009. (Best Student Paper Award).
Evolving Neural Networks for Strategic Decision-Making Problems 2009
Nate Kohl and Risto Miikkulainen, Neural Networks, Special issue on Goal-Directed Neural Systems (2009).
Evolving Symmetric and Modular Neural Network Controllers for Multilegged Robots 2009
Vinod K. Valsalam and Risto Miikkulainen, In xploring New Horizons in Evolutionary Design of Robots: Workshop at the 2009 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) 2009.
Evolving Symmetric and Modular Neural Networks for Distributed Control 2009
Vinod K. Valsalam and Risto Miikkulainen, In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO), pp. 731--738 2009.
Hyperlearning: A Connectionist Model of Psychosis in Schizophrenia 2009
Uli Grasemann, Risto Miikkulainen and Ralph Hoffman, In Proceedings of the 31st Annual Meeting of the Cognitive Science Society, N. A. Taatgen and H. van Rijn (Eds.), Amsterdam, The Netherlands 2009.
Learning Dynamic Obstacle Avoidance for a Robot Arm Using Neuroevolution 2009
Thomas D'Silva, Risto Miikkulainen, Neural Processing Letters (2009).
Learning in Fractured Problems for Constructive Neural Network Algorithms 2009
Nate Kohl, PhD Thesis, Department of Computer Sciences, University of Texas at Austin.
Modeling the Bilingual Lexicon of an Individual Subject 2009
Risto Miikkulainen and Swathi Kiran, In Proceedings of the Workshop on Self-Organizing Maps (WSOM'09), Berlin 2009. Springer.
Spherical Topic Models 2009
Joseph Reisinger, Austin Waters, Bryan Silverthorn, and Raymond Mooney, In NIPS'09 workshop: Applications for Topic Models: Text and Beyond 2009.
Temporal Convolution Machines for Sequence Learning 2009
Alan J Lockett and Risto Miikkulainen, Technical Report AI-09-04, Department of Computer Sciences, the University of Texas at Austin.
The Necessity of Separating Control and Logic When Grounding Language Using Neuroevolution 2009
Yonatan Bisk, Technical Report HR-09-05, Department of Computer Sciences, The University of Texas at Austin.
Accelerated Neural Evolution through Cooperatively Coevolved Synapses 2008
Faustino Gomez, Juergen Schmidhuber, and Risto Miikkulainen, Journal of Machine Learning Research (2008), pp. 937-965.
Category Learning Systems 2008
Dagmar Zeithamova, PhD Thesis, Institute for Neuroscience, The University of Texas at Austin.
Competition Between Reinforcement Learning Methods in a Predator-Prey Grid World 2008
Jacob Schrum, Technical Report AI08-9, The University of Texas at Austin, Department of Computer Sciences.
Constructing Complex NPC Behavior via Multi-Objective Neuroevolution 2008
Jacob Schrum and Risto Miikkulainen, In Proceedings of the Fourth Artificial Intelligence and Interactive Digital Entertainment Conference (AIIDE 2008), pp. 108-113, Stanford, California 2008.
Dissociable prototype learning systems: Evidence from brain imaging and behavior 2008
Dagmar Zeithamova, W. Todd Maddox and David M. Schnyer, Journal of Neuroscience, Vol. 28, 49 (2008), pp. 13194-13201.
Evolving Controllers for Simulated Car Racing using Neuroevolution 2008
Aravind Gowrisankar, Masters Thesis, Department of Computer Sciences, The University of Texas at Austin. 85 pages.
Evolving Neural Networks for Fractured Domains 2008
Nate Kohl and Risto Miikkulainen, In Proceedings of the Genetic and Evolutionary Computation Conference, pp. 1405-1412, July 2008.
Evolving Opponent Models for Texas Hold 'Em 2008
Alan J Lockett and Risto Miikkulainen, In IEEE Conference on Computational Intelligence in Games, Perth, Australia 2008.
Incremental Nonmonotonic Sentence Interpretation through Semantic Self-Organization 2008
Marshall R. Mayberry III and Risto Miikkulainen, Technical Report AI08-12, Department of Computer Sciences, University of Texas at Austin.
Memory Processes in Perceptual Decision Making 2008
Manish Saggar, Risto Miikkulainen, David M Schnyer, In Proceedings of the 30th Annual Conference of the Cognitive Science Society, Nashville, TN 2008.
Modular Neuroevolution for Multilegged Locomotion 2008
Vinod K. Valsalam and Risto Miikkulainen, In Proceedings of the Genetic and Evolutionary Computation Conference GECCO 2008, pp. 265-272, New York, NY, USA 2008. ACM.
Motion Perception and the Scene Statistics of Motion 2008
Tal Tversky, PhD Thesis, Department of Computer Science, The University of Texas at Austin.
Online Kernel Selection for Bayesian Reinforcement Learning 2008
Joseph Reisinger, Peter Stone, and Risto Miikkulainen, In Proceedings of the Twenty-Fifth International Conference on Machine Learning, July 2008.
Transfer of Evolved Pattern-Based Heuristics in Games 2008
Erkin Bahceci and Risto Miikkulainen, In IEEE Symposium On Computational Intelligence and Games (CIG 2008), pp. 220-227, Perth, Australia, December 2008.
A computational model of the motivation-learning interface 2007
Manish Saggar, Arthur B Markman, W Todd Maddox, Risto Miikkulainen, In Proceedings of the 29th Annual Conference of the Cognitive Science Society, Nashville, TN 2007.
A Computational Model of the Signals in Optical Imaging with Voltage-Sensitive Dyes 2007
Yiu Fai Sit and Risto Miikkulainen, Neurocomputing (2007), pp. 1853-1857.
A Subsymbolic Model of Language Pathology in Schizophrenia 2007
Uli Grasemann, Risto Miikkulainen, Ralph Hoffman, In Proceedings of the 29th Annual Conference of the Cognitive Science Society, pp. 311-316, Hillsdale, NJ 2007. Erlbaum.
Acquiring Evolvability through Adaptive Representations 2007
Joseph Reisinger and Risto Miikkulainen, In Proceeedings of the Genetic and Evolutionary Computation Conference, pp. 1045-1052 2007.
Acquiring Visibly Intelligent Behavior with Example-Guided Neuroevolution 2007
Bobby D. Bryant and Risto Miikkulainen, In Proceedings of the Twenty-Second National Conference on Artificial Intelligence, Menlo Park, CA 2007. AAAI Press.
Coevolution of Role-Based Cooperation in Multi-Agent Systems 2007
Chern Han Yong and Risto Miikkulainen, Technical Report AI07-338, Department of Computer Sciences, The University of Texas at Austin.
Coevolving Strategies for General Game Playing 2007
Joseph Reisinger, Erkin Bahceci, Igor Karpov and Risto Miikkulainen, In Proceedings of the {IEEE} Symposium on Computational Intelligence and Games, pp. 320-327, Piscataway, NJ 2007. IEEE.
Detecting Motion in the Environment with a Moving Quadruped Robot 2007
Peggy Fidelman, Thayne Coffman and Risto Miikkulainen, In RoboCup-2006: Robot Soccer World Cup X, Gerhard Lakemeyer and Elizabeth Sklar and Domenico Sorenti and Tomoichi Takahashi (Eds.), pp. 219-231, Berlin 2007. Springer Verlag.
Developing Complex Systems Using Evolved Pattern Generators 2007
Vinod K. Valsalam, James A. Bednar and Risto Miikkulainen, IEEE Transactions on Evolutionary Computation (2007), pp. 181-198.
Effects of Acquisition Rate on Emergent Structure in Phonological Development 2007
Melissa A. Redford and Risto Miikkulainen, Language (2007), pp. 737-769.
Evolving Explicit Opponent Models for Game Play 2007
Alan Lockett, Charles Chen, and Risto Miikkulainen, In Genetic and Evolutionary Computation Conference (GECCO-2007) 2007.
MARLEDA: Effective Distribution Estimation Through Markov Random Fields 2007
Matthew Alden, PhD Thesis, Department of Computer Sciences, the University of Texas at Austin. Also Technical Report AI07-349.
Modeling the self-organization of color selectivity in the visual cortex 2007
Judah Ben De Paula, PhD Thesis, Department of Computer Sciences, The University of Texas at Austin.
Reinforcement Learning in High-Diameter, Continuous Environments 2007
Jefferson Provost, PhD Thesis, Computer Sciences Department, University of Texas at Austin.
Self-Organizing Distinctive State Abstraction Using Options 2007
Jefferson Provost, Benjamin J. Kuipers, and Risto Miikkulainen, In Proceedings of the 7th International Conference on Epigenetic Robotics 2007.
Semantic Boost on Episodic Associations: An Empirically Based Computational Model 2007
Yaron Silberman, Shlomo Bentin, and Risto Miikkulainen, Cognitive Science, Vol. 31 (2007), pp. 645--671.
System Identification for the Hodgkin-Huxley Model using Artificial Neural Networks 2007
Manish Saggar, Tekin Mericli, Sari Andoni, Risto Miikkulainen, In Proceedings of International Joint Conference on Neural Networks, Orlando, Florida, August 2007.
Coevolution of Neural Networks using a Layered Pareto Archive 2006
German A. Monroy, Kenneth O. Stanley, Risto Miikkulainen, In Proceedings of the Genetic and Evolutionary Computation Conference, pp. 329-336, Seattle, Washington, July 2006. New York, NY: ACM Press.
Computational Intelligence in Games 2006
Risto Miikkulainen, Bobby D. Bryant, Ryan Cornelius, Igor V. Karpov, Kenneth O. Stanley, and Chern Han Yong, In Computational Intelligence: Principles and Practice, Gary Y. Yen and David B. Fogel (Eds.), Piscataway, NJ 2006. IEEE Computational Intelligence Society.
Converting RGB Images to LMS Cone Activations 2006
Judah B. De Paula, Technical Report, Department of Computer Sciences, The University of Texas at Austin. Technical Report 06-49.
Creating Intelligent Agents in Games 2006
Risto Miikkulainen, The Bridge (2006), pp. 5-13.
Developing navigation behavior through self-organizing distinctive state abstraction 2006
Jefferson Provost, Benjamin J. Kuipers, and Risto Miikkulainen, Connection Science, Vol. 18 (2006), pp. 159-172.
Efficient Non-Linear Control through Neuroevolution 2006
Faustino Gomez, Juergen Schmidhuber, and Risto Miikkulainen, In Proceedings of the European Conference on Machine Learning, pp. 654-662, Berlin 2006. Springer.
Establishing an Appropriate Learning Bias Through Development 2006
Vinod K. Valsalam, James A. Bednar, and Risto Miikkulainen, In Proceedings of the Fifth International Conference on Development and Learning (ICDL-2006) 2006.
Evolving a Real-World Vehicle Warning System 2006
Nate Kohl, Kenneth Stanley, Risto Miikkulainen, Michael Samples, and Rini Sherony, In Proceedings of the Genetic and Evolutionary Computation Conference 2006.
Evolving Robot Arm Controllers Using the NEAT Neuroevolution Method 2006
Thomas W. D'Silva, Masters Thesis, Department of Electrical and Computer Engineering, The University of Texas at Austin.
Evolving Stochastic Controller Networks for Intelligent Game Agents 2006
Bobby D. Bryant and Risto Miikkulainen, In Proceedings of the 2006 Congress on Evolutionary Computation, Piscataway, NJ 2006. IEEE.
Evolving Visibly Intelligent Behavior for Embedded Game Agents 2006
Bobby D. Bryant, PhD Thesis, Department of Computer Sciences, The University of Texas at Austin. Technical Report AI-06-334.
Exploiting Sensor Symmetries in Example-based Training for Intelligent Agents 2006
Bobby D. Bryant and Risto Miikkulainen, In Proceedings of the {IEEE} Symposium on Computational Intelligence and Games, Sushil M. Louis and Graham Kendall (Eds.), pp. 90-97, Piscataway, NJ 2006. IEEE.
Grounding Language in Descriptions of Scenes 2006
Paul Williams and Risto Miikkulainen, In Proceedings of the 28th Annual Meeting of the Cognitive Science Society 2006.
Incorporating Advice into Neuroevolution of Adaptive Agents 2006
Chern Han Yong, Kenneth O. Stanley, Risto Miikkulainen, and Igor V. Karpov, In Proceedings of the Second Artificial Intelligence and Interactive Digital Entertainment Conference, pp. 98-104, Menlo Park, CA 2006. AAAI Press.
Integration and Evaluation of Exploration-Based Learning in Games 2006
Igor V. Karpov, Thomas D'Silva, Craig Varrichio, Kenneth O. Stanley, Risto Miikkulainen, In Proceedings of the {IEEE} Symposium on Computational Intelligence and Games, Reno, NV 2006. IEEE.
Joint Maps for Orientation, Eye, and Direction Preference in a Self-Organizing Model of V1 2006
James A. Bednar and Risto Miikkulainen, Neurocomputing, Vol. 69 (2006), pp. 1272--1276.
Prenatal Development of Ocular Dominance and Orientation Maps in a Self-Organizing Model of V1 2006
Stefanie Jegelka, James A. Bednar, and Risto Miikkulainen, Neurocomputing, Vol. 69 (2006), pp. 1291--1296.
Real-Time Evolution of Neural Networks in the NERO Video Game 2006
Kenneth O. Stanley, Bobby D. Bryant, Igor Karpov, Risto Miikkulainen, In Proceedings of the Twenty-First National Conference on Artificial Intelligence (AAAI-2006), pp. 1671--1674, Boston, MA 2006. Meno Park, CA: AAAI Press.
Selecting for Evolvable Representations 2006
Joseph Reisinger and Risto Miikkulainen, In Proceedings of the Genetic and Evolutionary Computation Conference 2006.
Self-Organization of Hierarchical Visual Maps with Feedback Connections 2006
Yiu Fai Sit and Risto Miikkulainen, Neurocomputing, Vol. 69 (2006), pp. 1309-1312.
The Effect of Delivery Method on Conceptual and Strategy Development 2006
Lisa C. Kaczmarczyk, Mary Z. Last, Risto Miikkulainen, In Proceedings of the 28th Annual Conference of the Cognitive Science Society 2006.
A Subsymbolic Model of Complex Story Understanding 2005
Peggy Fidelman, Risto Miikkulainen and Ralph Hoffman, In Proceedings of the 27th Annual Meeting of the Cognitive Science Society 2005.
Academic AI and Video Games: A Case Study of Incorporating Innovative Academic Research into a Video Game Prototype 2005
Aliza Gold, In Proceedings of the IEEE 2005 Symposium on Computational Intelligence and Games (CIG'05) 2005. Piscataway, NJ: IEEE.
Automatic Feature Selection via Neuroevolution 2005
Shimon Whiteson, Peter Stone, Kenneth O. Stanley, Risto Miikkulainen, and Nate Kohl, In Proceedings of the Genetic and Evolutionary Computation Conference, June 2005.
Broad-Coverage Parsing with Neural Networks 2005
Marshall R. Mayberry III and Risto Miikkulainen, Neural Processing Letters, Vol. 21 (2005), pp. 121--143.
Coevolution of Neural Networks Using a Layered Pareto Archive 2005
German A. Monroy, Masters Thesis, Department of Computer Sciences, The University of Texas at Austin.
Constructing Good Learners Using Evolved Pattern Generators 2005
Vinod K. Valsalam, James A. Bednar, and Risto Miikkulainen, In Proceedings of the Genetic and Evolutionary Computation Conference, GECCO-2005, H.-G. Beyer and others (Eds.), pp. 11-18 2005.
Constructing Visual Function Through Prenatal and Postnatal Learning 2005
James A. Bednar and Risto Miikkulainen, In Neuroconstructivism, Vol. 2: Perspectives and Prospects, Denis Mareschal and Mark H. Johnson and Sylvain Sirois and Michael Spratling and Michael S. C. Thomas and Gert Westermann (Eds.), pp....
Effective Image Compression Using Evolved Wavelets 2005
Uli Grasemann and Risto Miikkulainen, In Proceedings of the Genetic and Evolutionary Computation Conference 2005.
Evolving Keepaway Soccer Players through Task Decomposition 2005
Shimon Whiteson, Nate Kohl, Risto Miikkulainen, and Peter Stone, Machine Learning, Vol. 59, 1 (2005), pp. 5-30.
Evolving Neural Network Agents in the NERO Video Game 2005
Kenneth O. Stanley, Bobby D. Bryant, and Risto Miikkulainen, In Proceedings of the IEEE 2005 Symposium on Computational Intelligence and Games (CIG'05), Piscataway, NJ 2005. IEEE.
Evolving Neural Network Ensembles for Control Problems 2005
David Pardoe, Michael Ryoo, and Risto Miikkulainen, In Proceedings of the Genetic and Evolutionary Computation Conference 2005.
Improving Prescripted Agent Behavior with Neuroevolution 2005
Ryan Cornelius, Technical Report HR-05-01, Department of Computer Sciences, The University of Texas at Austin.
Incorporating Advice into Evolution of Neural Networks 2005
Chern Han Yong, Kenneth O. Stanley, and Risto Miikkulainen, In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2005) 2005. Late Breaking Papers.
Learning Basic Navigation for Personal Satellite Assistant Using Neuroevolution 2005
Yiu Fai Sit and Risto Miikkulainen, In Proceedings of the Genetic and Evolutionary Computation Conference 2005.
Learning Visual Scene Descriptions: An Approach to Symbol Grounding 2005
Paul Williams, Technical Report TR-06-01, Department of Computer Science, The University of Texas at Austin.
Neuroevolution of an Automobile Crash Warning System 2005
Kenneth Stanley, Nate Kohl, Rini Sherony, and Risto Miikkulainen, In Proceedings of the Genetic and Evolutionary Computation Conference 2005.
Real-Time Learning in the NERO Video Game 2005
Kenneth O. Stanley, Ryan Cornelius, Risto Miikkulainen, Thomas D'Silva, and Aliza Gold, In Proceedings of the Artificial Intelligence and Interactive Digital Entertainment Conference (AIIDE 2005) Demo Papers 2005.
Real-time Neuroevolution in the NERO Video Game 2005
Kenneth O. Stanley, Bobby D. Bryant, and Risto Miikkulainen, IEEE Transactions on Evolutionary Computation (2005), pp. 653-668. IEEE.
Retaining Learned Behavior During Real-Time Neuroevolution 2005
Thomas D'Silva, Roy Janik, Michael Chrien, Kenneth O. Stanley and Risto Miikkulainen, Artificial Intelligence and Interactive Digital Entertainment (2005). American Association for Artificial Intelligence.
Self-organization of color opponent receptive fields and laterally connected orientation maps 2005
James A. Bednar, Judah B. De Paula, and Risto Miikkulainen, Neurocomputing, Vol. 65--66 (2005), pp. 69-76.
The Acquisition of Intellectual Expertise: A Computational and Empirical Theory 2005
Elizabeth C. Kaczmarczyk, PhD Thesis, Department of Computer Sciences, University of Texas at Austin.
Towards an Empirical Measure of Evolvability 2005
Joseph Reisinger, Kenneth O. Stanley, Risto Miikkulainen, In Genetic and Evolutionary Computation Conference {(GECCO2005)} Workshop Program, pp. 257-264, Washington, D.C. 2005. ACM Press.
Self-Organizing Perceptual and Temporal Abstraction for Robot Reinforcement Learning 2004
Jefferson Provost, Benjamin J. Kuipers and Risto Miikkulainen, In AAAI-04 Workshop on Learning and Planning in Markov Processes 2004.
A Neurocontrol Paradigm for Intelligent Process Control using Evolutionary Reinforcement Learning 2004
Alex van Eck Conradie, PhD Thesis, Department of Chemical Engineering, University of Stellenbosch.
Competitive Coevolution through Evolutionary Complexification 2004
Kenneth O. Stanley and Risto Miikkulainen, Journal of Artificial Intelligence Research, Vol. 21 (2004), pp. 63-100.
Contour grouping: closure effects are explained by good continuation and proximity 2004
Tal Tversky, Wilson S. Geisler and Jeffrey S. Perry, Vision Research, Vol. 44, 24 (2004), pp. 2769--2777.
Contour Integration and Segmentation with Self-Organized Lateral Connections 2004
Yoonsuck Choe and Risto Miikkulainen, Biological Cybernetics 90:75-88
Efficient Allele Fitness Assignment with Self-organizing Multi-agent System 2004
Adrian Agogino and Risto Miikkulainen, In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO-2004) Workshop Program, New York, NY 2004. Springer-Verlag.
Efficient Evolution of Neural Networks Through Complexification 2004
Kenneth O. Stanley, PhD Thesis, Department of Computer Sciences, The University of Texas at Austin.
Evolving a Roving Eye for Go 2004
Kenneth O. Stanley and Risto Miikkulainen, In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO-2004), Berlin 2004. Springer Verlag.
Evolving Reusable Neural Modules 2004
Joseph Reisinger, Kenneth O. Stanley, and Risto Miikkulainen, In Proceedings of the Genetic and Evolutionary Computation Conference 2004.
Evolving Wavelets using a Coevolutionary Genetic Algorithm and Lifting 2004
Uli Grasemann and Risto Miikkulainen, In Proceedings of the Genetic and Evolutionary Computation Conference, pp. 969-980, San Francisco 2004. Kaufmann.
Exploiting Morphological Conventions for Genetic Reuse 2004
Kenneth O. Stanley, Joseph Reisinger, and Risto Miikkulainen, In Proceedings of the Genetic and Evolutionary Computation Conference ({GECCO}-2004) Workshop Program, Berlin 2004. Springer Verlag.
Loop-closing and planarity in topological map-building 2004
Francesco Savelli and Benjamin Kuipers, In IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS-04), pp. 1511--1517 2004.
Modeling Cortical Maps with Topographica 2004
James A. Bednar, Yoonsuck Choe, Judah De Paula, Risto Miikkulainen, Jefferson Provost, and Tal Tversky, Neurocomputing (2004), pp. 1129-1135.
Prenatal and Postnatal Development of Laterally Connected Orientation Maps 2004
James A. Bednar and Risto Miikkulainen, Neurocomputing, Vol. 58-60 (2004), pp. 985-992.
The Acquisition of Intellectual Expertise: A Computational Model 2004
Elizabeth C. Kaczmarczyk, Risto Miikkulainen, In Proceedings of the 26th Annual Conference of the Cognitive Science Society 2004.
The Constructivist Learning Architecture: A Model of Cognitive Development for Robust Autonomous Robots 2004
Harold H. Chaput, PhD Thesis, Department of Computer Sciences, The University of Texas at Austin. Also Technical Report TR-04-34.
Transfer of Neuroevolved Controllers in Unstable Domains 2004
Faustino J. Gomez and Risto Miikkulainen, In Proceedings of the Genetic and Evolutionary Computation Conference, Berlin 2004. Springer.
A Taxonomy for Artificial Embryogeny 2003
Kenneth O. Stanley and Risto Miikkulainen, Artificial Life, Vol. 9, 2 (2003), pp. 93-130.
Achieving High-Level Functionality through Evolutionary Complexification 2003
Kenneth O. Stanley and Risto Miikkulainen, In Proceedings of the AAAI-2003 Spring Symposium on Computational Synthesis, Stanford, CA 2003. AAAI Press.
Active Guidance for a Finless Rocket Using Neuroevolution 2003
Faustino J. Gomez and Risto Miikkulainen, In Proceedings of the Genetic and Evolutionary Computation Conference, pp. 2084-2095, San Francisco 2003. Morgan Kaufmann.
Constructivist Learning: A Neural Implementation of the Schema Mechanism 2003
Harold H. Chaput, Benjamin Kuipers and Risto Miikkulainen, In Proceedings of WSOM '03: Workshop for Self-Organizing Maps, Kitakyushu, Japan 2003.
Evolving Adaptive Neural Networks with and Without Adaptive Synapses 2003
Kenneth O. Stanley, Bobby D. Bryant, and Risto Miikkulainen, In Proceedings of the 2003 Congress on Evolutionary Computation, Piscataway, NJ 2003. IEEE.
Incremental Nonmonotonic Parsing through Semantic Self-Organization 2003
Marshall R. Mayberry III, PhD Thesis, Department of Computer Sciences, the University of Texas at Austin. Technical Report AI-TR-04-310.
Incremental Nonmonotonic Parsing through SemanticSelf-Organization 2003
Marshall R. Mayberry III and Risto Miikkulainen, In Proceedings of the 25th Annual Conference of the Cognitive Science Society 2003.
Learning Concept Drift with a Committee of Decision Trees 2003
Kenneth O. Stanley, Technical Report AI03-302, Department of Computer Sciences, The University of Texas at Austin.
Learning Innate Face Preferences 2003
James A. Bednar and Risto Miikkulainen, Neural Computation, Vol. 15, 7 (2003), pp. 1525-1557.
Neuroevolution for Adaptive Teams 2003
Bobby D. Bryant and Risto Miikkulainen, In Proceedings of the 2003 Congress on Evolutionary Computation (CEC 2003), pp. 2194-2201, Piscataway, NJ 2003. IEEE.
PhD Thesis: Robust Non-Linear Control through Neuroevolution 2003
Faustino J. Gomez, Technical Report AI-TR-03-303, Department of Computer Sciences, University of Texas at Austin.
Robust Non-Linear Control through Neuroevolution 2003
Faustino J. Gomez, PhD Thesis, Department of Computer Sciences, The University of Texas at Austin.
Self-Organization of Spatiotemporal Receptive Fields and Laterally Connected Direction and Orientation Maps 2003
James A. Bednar and Risto Miikkulainen, Neurocomputing, Vol. 52--54 (2003), pp. 473-480.
The Role of Internally Generated Neural Activity in Newborn and Infant Face Preferences 2003
James A. Bednar, In Face Perception in Infancy and Early Childhood, Olivier Pascalis and Alan Slater (Eds.), pp. 133-142, New York 2003. NOVA Science Publishers.
Utilizing Domain Knowledge in Neuroevolution 2003
James Fan, Raymond Lau, and Risto Miikkulainen, Proceedings of the Twentieth International Conference on Machine Learning (ICML-03, Washington, DC)
Adaptive Control Utilising Neural Swarming 2002
Alex v. E. Conradie, Risto Miikkulainen, and Christiaan Aldrich, In Proceedings of the Genetic and Evolutionary Computation Conference, William B. Langdon and Erick Cantu-Paz and Keith E. Mathias and Rajkumar Roy and David Davis and Riccardo Poli and Karth...
Continual Coevolution Through Complexification 2002
Kenneth O. Stanley and Risto Miikkulainen, In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO-2002), William B. Langdon and Erick Cantu-Paz and Keith E. Mathias and Rajkumar Roy and David Davis and Riccardo Pol...
Cultural Enhancement Of Neuroevolution 2002
Paul H. McQuesten, PhD Thesis, Department of Computer Sciences, The University of Texas at Austin. Technical Report AI-02-295.
Efficient Evolution Of Neural Network Topologies 2002
Kenneth O. Stanley and Risto Miikkulainen, In Proceedings of the Genetic and Evolutionary Computation Conference, William B. Langdon and Erick Cantu-Paz and Keith E. Mathias and Rajkumar Roy and David Davis and Riccardo Poli and Karthik...
Efficient Reinforcement Learning Through Evolving Neural Network Topologies 2002
Kenneth O. Stanley and Risto Miikkulainen, In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO-2002), pp. 9, San Francisco 2002. Morgan Kaufmann.
Eugenic Evolution Utilizing A Domain Model 2002
Matthew Alden, Aard-Jan van Kesteren, and Risto Miikkulainen, In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2002), pp. 279-286 2002.
Evolving Neural Networks Through Augmenting Topologies 2002
Kenneth O. Stanley and Risto Miikkulainen, Evolutionary Computation, Vol. 10, 2 (2002), pp. 99-127.
Intelligent Process Control Utilizing Symbiotic Memetic Neuro-Evolution 2002
Alex v. E. Conradie, Risto Miikkulainen, and Christiaan Aldrich, In Proceedings of the 2002 Congress on Evolutionary Computation, pp. 6 2002.
Learning to See: Genetic and Environmental Influences on Visual Development 2002
James A. Bednar, PhD Thesis, Department of Computer Sciences, The University of Texas at Austin. Also Technical Report AI-TR-02-294.
Modeling Directional Selectivity Using Self-Organizing Delay-Adaptation Maps 2002
Tal Tversky and Risto Miikkulainen, Neurocomputing, Vol. 44--46 (2002), pp. 679--684. Also in J. M. Bower (editor), Computational Neuroscience: Trends in Research, 2002 (CNS*01, Pacific Grove, CA). New York: Elsevier.
Modeling Large Cortical Networks With Growing Self-Organizing Maps 2002
James A. Bednar, Amol Kelkar, and Risto Miikkulainen, Neurocomputing, Vol. 44--46 (2002), pp. 315-321.
Neonatal Learning Of Faces: Environmental And Genetic Influences 2002
James A. Bednar and Risto Miikkulainen, In Proceedings of the 24th Annual Conference of the Cognitive Science Society, pp. 107-112 2002.
Neuroevolution through Augmenting Topologies Applied to Evolving Neural Networks to Play Othello 2002
Timothy Andersen, Technical Report HR-02-01, Department of Computer Sciences, The University of Texas at Austin.
Numerical Optimization With Neuroevolution 2002
Brian Greer, Henri Hakonen, Risto Lahdelma, and Risto Miikkulainen, In Proceedings of the 2002 Congress on Evolutionary Computation, pp. 361-401, Piscataway, NJ 2002. IEEE. Undergraduate Thesis, Department of Computer Sciences, The University of Texas at Aust...
Text and Discourse Understanding: The DISCERN System 2002
Risto Miikkulainen, In A Handbook of Natural Language Processing: Techniques and Applications for the Processing of Language as Text, R. Dale, H. Moisl and H. Somers (Eds.), pp. 905--919, New York 2002.
The Dominance Tournament Method of Monitoring Progress in Coevolution 2002
Kenneth O. Stanley and Risto Miikkulainen, In Proceedings of the Genetic and Evolutionary Computation Conference ({GECCO}-2002) Workshop Program, pp. 7, San Francisco 2002. Morgan Kaufmann.
A Model Of Infant Causal Perception And Its Development 2001
Harold H. Chaput and Leslie B. Cohen, In Proceedings of the 23rd Annual Conference of the Cognitive Science Society, pp. 182-187 2001.
A Neuroevolution Method For Dynamic Resource Allocation On A Chip Multiprocessor 2001
Faustino J. Gomez, Doug Burger, and Risto Miikkulainen, In Proceedings of the {INNS-IEEE} International Joint Conference on Neural Networks, pp. 2355-2361, Piscataway, NJ 2001. IEEE.
Abrupt And Gradual Sound Change In An Expanding Lexicon 2001
Melissa A. Redford and Risto Miikkulainen, Technical Report AI01-289, Department of Computer Sciences, The University of Texas at Austin.
Applying ESP And Region Specialists To Neuro-Evolution For Go 2001
Andres Santiago Perez-Bergquist, Technical Report TR-01-24, Department of Computer Science, University of Texas at Austin.
Co-Evolving A Go-Playing Neural Network 2001
Alex Lubberts and Risto Miikkulainen, In Coevolution: {T}urning Adaptive Algorithms Upon Themselves, Birds-of-a-Feather Workshop, Genetic and Evolutionary Computation Conference ({GECCO}-2001), pp. 6 2001.
Constrained Emergence Of Universals And Variation In Syllable Systems 2001
Melissa A. Redford, Chun Chi Chen, and Risto Miikkulainen, Language and Speech (2001), pp. 27-56. Manuscript.
Cooperative Coevolution Of Multi-Agent Systems 2001
Chern Han Yong and Risto Miikkulainen, Technical Report AI07-338, Department of Computer Sciences, The University of Texas at Austin.
Creating Melodies With Evolving Recurrent Neural Networks 2001
Chun-Chi J. Chen and Risto Miikkulainen, In Proceedings of the {INNS-IEEE} International Joint Conference on Neural Networks, pp. 2241-2246, Piscataway, NJ 2001. IEEE.
Evolving Populations Of Expert Neural Networks 2001
Joseph Bruce and Risto Miikkulainen, In Proceedings of the Genetic and Evolutionary Computation Conference, pp. 251-257, San Francisco, CA 2001. Morgan Kaufmann.
From Word Stream To Gestalt: A Direct Semantic Parse For Complex Sentences 2001
Bobby D. Bryant and Risto Miikkulainen, Technical Report AI98-274, AI Lab, University of Texas at Austin.
Numerical Optimization with Neuroevolution 2001
Brian Greer, Technical Report TR-01-49, Department of Computer Science, The University of Texas at Austin.
Perceptual Grouping In A Self-Organizing Map Of Spiking Neurons 2001
Yoonsuck Choe, PhD Thesis, Department of Computer Sciences, The University of Texas at Austin. 133. Technical Report AI01-292.
Post-Piagetian constructivism for grounded knowledge acquisition 2001
Harold H. Chaput, In Proceedings of the AAAI Spring Symposium Series on Grounded Knoweldge, Palo Alto, CA 2001.
Scaling Self-Organizing Maps To Model Large Cortical Networks 2001
James A. Bednar, Amol Kelkar, and Risto Miikkulainen, Neuroinformatics (2001), pp. 275-302.
Semantic Effect On Episodic Associations 2001
Yaron Silberman, Risto Miikkulainen, and Shlomo Bentin, In Proceedings of the 23rd Annual Conference of the Cognitive Science Society, pp. 934-939 2001.
Toward Learning the Causal Layer of the Spatial Semantic Hierarchy using SOMs 2001
Jefferson Provost, Patrick Beeson, and Benjamin J. Kuipers, In AAAI Spring Symposium Series, Learning Grounded Representations 2001.
A Self-Organizing Neural Network For Contour Integration Through Synchronized Firing 2000
Yoonsuck Choe and Risto Miikkulainen, Proceedings of the 17th National Conference on Artificial Intelligence (AAAI-2000, Austin, TX), 123-128. Cambridge, MA: MIT Press, 2000
Automatic Music Composition using Genetic Algorithm and Neural Networks: A Constrained Evolution Approach 2000
Chun-Chi Chen, Technical Report HR-00-02, Department of Computer Sciences, The University of Texas at Austin.
Cooperative Coevolution of Multi-Agent Systems 2000
Chern Han Yong, Technical Report HR-00-01, Department of Computer Sciences, The University of Texas at Austin.
Effects Of Presynaptic And Postsynaptic Resource Redistribution In Hebbian Weight Adaptation 2000
Yoonsuck Choe, Risto Miikkulainen, and Lawrence K. Cormack, Neurocomputing, Vol. 32--33 (2000), pp. 77-82.
Eugenic Neuro-Evolution For Reinforcement Learning 2000
Daniel Polani and Risto Miikkulainen, In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO-2000), pp. 1041-1046, San Francisco 2000. Morgan Kaufmann.
Hebbian Learning And Temporary Storage In The Convergence-Zone Model Of Episodic Memory 2000
Michael Howe and Risto Miikkulainen, Neurocomputing, Vol. 32--33 (2000), pp. 817--821. Also J. M. Bower (editor), Computational Neuroscience: Trends in Research, 2000 (CNS*99, Pittsburgh, PA). New York: Plenum Press..
Internally-Generated Activity, Non-Episodic Memory, and Emotional Salience in Sleep 2000
James A. Bednar, Behavioral and Brain SciencesS. Harnad and E. Pace-Schott and M. Blagrove and M. Solms (Eds.) (2000), pp. 119-120. Cambridge University Press. Commentary on the 'Sleep and Dreaming' issue..
Neuro-Evolution And Natural Deduction 2000
Nirav S. Desai and Risto Miikkulainen, In Proceedings of The First {IEEE} Symposium on Combinations of Evolutionary Computation and Neural Networks, pp. 64-69, Piscataway, NJ 2000. IEEE.
Online Interactive Neuro-Evolution 2000
Adrian Agogino, Kenneth O. Stanley, and Risto Miikkulainen, Neural Processing Letters (2000), pp. 29-38.
Self-Organization Of Innate Face Preferences: Could Genetics Be Expressed Through Learning? 2000
James A. Bednar and Risto Miikkulainen, In Proceedings of the 17th National Conference on Artificial Intelligence and the 12th Annual Conference on Innovative Applications of Artificial Intelligence, pp. 117-122 2000.
Tilt Aftereffects In A Self-Organizing Model Of The Primary Visual Cortex 2000
James A. Bednar and Risto Miikkulainen, Neural Computation, Vol. 12 (2000), pp. 1721-1740.
Confidence Based Dual Reinforcement Q-Routing: An Adaptive On-Line Routing Algorithm 1999
Shailesh Kumar and Risto Miikkulainen, In 16th International Joint Conference on Artificial Intelligence (IJCAI-99), pp. 758--763, Stockholm, Sweden 1999. San Francisco, CA: Kaufmann.
Disambiguation And Grammar As Emergent Soft Constraints 1999
Risto Miikkulainen and Marshall R. Mayberry III, In Workshop on Thought and Language, Brian J. MacWhinney (Eds.), pp. 20-31, Iizuka, Japan 1999. Department of Artificial Intelligence, Kyushu Institute of Technology.
Modeling The Self-Organization Of Directional Selectivity In The Primary Visual Cortex 1999
Igor Farkas and Risto Miikkulainen, In Proceedings of the Ninth International Conference on Artificial Neural Networks, Erkki Oja and Samuel Kaski (Eds.), pp. 251-256, Amsterdam 1999. Elsevier.
SARDSRN: A Neural Network Shift-Reduce Parser 1999
Marshall R. Mayberry III and Risto Miikkulainen, In Proceedings of the 16th Annual International Joint Conference on Artificial Intelligence (IJCAI-99), pp. 820-825, Stockholm, Sweden 1999. San Francisco, CA: Kaufmann.
Solving Non-Markovian Control Tasks With Neuroevolution 1999
Faustino J. Gomez and Risto Miikkulainen, unpublished. Dissertation Proposal, Computer Science Department, University of Texas at Austin.
Using a Sequential SOM to Parse Long-Term Dependencies 1999
Marshall R. Mayberry III and Risto Miikkulainen, In Proceedings of the 21st Annual Conference of the Cognitive Science Society, Martin Hahn and Scott C. Stoness (Eds.), pp. 367-372 1999. Hillsdale, NJ: Erlbaum.
2-D Pole Balancing With Recurrent Evolutionary Networks 1998
Faustino Gomez and Risto Miikkulainen, In Proceedings of the International Conference on Artificial Neural Networks (ICANN-98), pp. 425-430, Skovde, Sweden 1998. Berlin, New York: Springer.
A Self-Organizing Neural Network Model of the Primary Visual Cortex 1998
Risto Miikkulainen, James Bednar, Yoonsuck Choe, and Joseph Sirosh, In Proceedings of the Fifth International Conference on Neural Information Processing (ICONIP'98), Volume 2, S. Usui, T. Omori (Eds.), pp. 815-818, Kitakyushu, Japan 1998.
Confidence Based Dual Reinforcement Q-Routing: An On-Line Adaptive Network Routing Algorithm 1998
Shailesh Kumar, Masters Thesis, Department of Computer Sciences, the University of Texas at Austin.. 108. Technical Report AI-98-267.
Confidence Based Q-Routing: An On-Line Adaptive Network Routing Algorithm 1998
Shailesh Kumar and Risto Miikkulainen, Smart Engineering Systems: Neural Networks, Fuzzy Logic, Data Mining, and Evolutionary ProgrammingC. H. Dagli and M. Akay and O. Ersoy and B. R. Fernandez and A. Smith (Eds.), Vol. 8 (1998).
Eugenic Evolution For Combinatorial Optimization 1998
John W. Prior, Masters Thesis, Department of Computer Sciences, The University of Texas at Austin. 126. Technical Report AI98-268.
Evolving Hierarchical Neural Networks to Play Go 1998
Todd Greer, Technical Report HR-94-01, Department of Computer Science, The University of Texas at Austin.
Evolving Neural Networks To Play Go 1998
Norman Richards, David Moriarty, and Risto Miikkulainen, Applied IntelligenceThomas B{"a}ck (Eds.) (1998), pp. 768-775. San Francisco, CA: Morgan Kaufmann.
Hierarchical Evolution Of Neural Networks 1998
David E. Moriarty and Risto Miikkulainen, In Proceedings of the 1998 IEEE Conference on Evolutionary Computation (ICEC98), pp. 428-433, Anchorage, AK 1998. Piscataway, NJ: IEEE.
Intrusion Detection With Neural Networks 1998
Jake Ryan, Meng-Jang Lin, and Risto Miikkulainen, In Advances in Neural Information Processing Systems 10, Michael I. Jordan and Michael J. Kearns and Sara A. Solla (Eds.), pp. 943-949 1998. Cambridge, MA: MIT Press.
Modeling The Emergence Of Syllable Systems 1998
Melissa A. Redford, Chun Chi Chen, and Risto Miikkulainen, In Proceedings of the 20th Annual Conference of the Cognitive Science Society, Morton Ann Gernsbacher and Sharon J. Derry (Eds.), pp. 882-886 1998. Hillsdale, NJ: Erlbaum.
Pattern-Generator-Driven Development In Self-Organizing Models 1998
James A. Bednar and Risto Miikkulainen, In Computational Neuroscience: Trends in Research, 1998, pp. 317-323 1998.
Self-Organization And Segmentation In A Laterally Connected Orientation Map Of Spiking Neurons 1998
Yoonsuck Choe and Risto Miikkulainen, Neurocomputing (1998), pp. 139-157.
Convergence-Zone Episodic Memory: Analysis And Simulations 1997
Mark Moll and Risto Miikkulainen, Neural Networks, Vol. 10 (1997), pp. 1017--1036.
Culling And Teaching In Neuro-Evolution 1997
Paul McQuesten and Risto Miikkulainen, In Proceedings of the Seventh International Conference on Genetic Algorithms (ICGA-97, East Lansing, MI), Thomas B{"a}ck (Eds.), pp. 760-767 1997. San Francisco, CA: Morgan Kaufmann.
Dual Reinforcement Q-Routing: An On-Line Adaptive Routing Algorithm 1997
Shailesh Kumar and Risto Miikkulainen, Smart Engineering Systems: Neural Networks, Fuzzy Logic, Data Mining, and Evolutionary ProgrammingC. H. Dagli, M. Akay, O. Ersoy, B. R. Fernandez and A. Smith (Eds.), Vol. 7 (1997).
Dyslexic and Category-Specific Aphasic Impairments in a Self-Organizing Feature Map Model of the Lexicon 1997
Risto Miikkulainen, Brain and Language (1997), pp. 334-366.
Forming Neural Networks Through Efficient And Adaptive Coevolution 1997
David E. Moriarty and Risto Miikkulainen, Evolutionary Computation, Vol. 5 (1997), pp. 373--399.
Incremental Evolution Of Complex General Behavior 1997
Faustino Gomez and Risto Miikkulainen, Adaptive Behavior, 5 (1997), pp. 317-342.
Natural Language Processing With Subsymbolic Neural Networks 1997
Risto Miikkulainen, In Neural Network Perspectives on Cognition and Adaptive Robotics, Antony Browne (Eds.), pp. 120-139, Bristol, UK; Philadelphia, PA 1997. Institute of Physics Publishing.
Self-Organization And Segmentation With Laterally Connected Spiking Neurons 1997
Yoonsuck Choe and Risto Miikkulainen, In Proceedings of the 15th International Joint Conference on Artificial Intelligence (IJCAI-97), pp. 1120-1125, Nagoya, Japan 1997. San Francisco: Kaufmann.
Self-Organization, Plasticity, and Low-Level Visual Phenomena in a Laterally Connected Map Model of the Primary Visual Cortex 1997
Risto Miikkulainen, James A. Bednar, Yoonsuck Choe, and Joseph Sirosh, In Perceptual Learning, R. L. Goldstone and P. G. Schyns and D. L. Medin (Eds.), pp. 257-308 1997.
Symbiotic Evolution Of Neural Networks In Sequential Decision Tasks 1997
David E. Moriarty, PhD Thesis, Department of Computer Sciences, The University of Texas at Austin. 117. Technical Report UT-AI97-257.
Tilt Aftereffects in a Self-Organizing Model of the Primary Visual Cortex 1997
James A. Bednar, Masters Thesis, Department of Computer Sciences, The University of Texas at Austin. Technical Report AI97-259.
Visual Schemas In Neural Networks For Object Recognition And Scene Analysis 1997
Wee Kheng Leow, Risto Miikkulainen, Connection ScienceMichael A. Arbib (Eds.) (1997), pp. 1029-1031. MIT Press.
Efficient Reinforcement Learning Through Symbiotic Evolution 1996
David E. Moriarty and Risto Miikkulainen, Machine LearningLeslie Pack Kaelbling (Eds.), AI94-224 (1996), pp. 11-32.
Evolving Obstacle Avoidance Behavior In A Robot Arm 1996
David E. Moriarty and Risto Miikkulainen, In From Animals to Animats 4: Proceedings of the Fourth International Conference on Simulation of Adaptive Behavior, Pattie Maes and Maja J. Mataric and Jean-Arcady Meyer and Jordan Pollack an...
Introduction: The Emerging Understanding of Lateral Interactions in the Cortex 1996
Risto Miikkulainen and Joseph Sirosh, In Lateral Interactions in the Cortex: Structure and Function, Sirosh, J., Miikkulainen, R., and Choe, Y. (Eds.) 1996. Electronic book, http://nn.cs.utexas.edu/web-pubs/htmlbook96.
Lateral Interactions In The Cortex: Structure And Function 1996
Joseph Sirosh, Risto Miikkulainen, and Yoonsuck Choe (editors), Electronic book, ISBN 0-9647060-0-8, http://nn.cs.utexas.edu/web-pubs/htmlbook96/. Austin, TX: The UTCS Neural Networks Research Group
Laterally Interconnected Self-Organizing Maps In Hand-Written Digit Recognition 1996
Yoonsuck Choe, Joseph Sirosh, and Risto Miikkulainen, In Advances in Neural Information Processing Systems 8, David S. Touretzky and Michael C. Mozer and Michael E. Hasselmo (Eds.), pp. 736-742 1996. Cambridge, MA: MIT Press.
On-Line Adaptation Of A Signal Predistorter Through Dual Reinforcement Learning 1996
Patrick Goetz, Shailesh Kumar and Risto Miikkulainen, In Machine Learning: Proceedings of the 13th Annual Conference (Bari, Italy), Lorenza Saitta (Eds.), pp. 175-181 1996. San Francisco, CA: Morgan Kaufmann.
Self-Organization and Functional Role of Lateral Connections and Multisize Receptive Fields in the Primary Visual Cortex 1996
Joseph Sirosh and Risto Miikkulainen, Neural Processing Letters, Vol. 3 (1996), pp. 39-48.
Self-Organization of Orientation Maps, Lateral Connections, and Dynamic Receptive Fields in the Primary Visual Cortex 1996
Joseph Sirosh, Risto Miikkulainen and James A. Bednar, In {P}roceedings of the {I}nternational {C}onference {on} {A}rtificial {N}eural {N}etworks, Joseph Sirosh and Risto Miikkulainen and Yoonsuck Choe (Eds.), pp. 1147-1152, Berlin 1996. Springer...
Subsymbolic Case-Role Analysis Of Sentences With Embedded Clauses 1996
Risto Miikkulainen, Cognitive Science, Vol. 20 (1996), pp. 47-73.
Topographic Receptive Fields and Patterned Lateral Interaction in a Self-Organizing Model of the Primary Visual Cortex 1996
Joseph Sirosh and Risto Miikkulainen, Neural Computation, Vol. 9 (1996), pp. 577-594.
A Model Of Visually Guided Plasticity Of The Auditory Spatial Map In The Barn Owl 1995
Andrea Haessly, Joseph Sirosh and Risto Miikkulainen, In Proceedings of the 17th Annual Conference of the Cognitive Science Society, pp. 154-158 1995. Hillsdale, NJ: Erlbaum.
A Self-Organizing Neural Network Model Of The Primary Visual Cortex 1995
Joseph Sirosh, PhD Thesis, Department of Computer Sciences, The University of Texas at Austin. Technical Report AI95-237.
Discovering Complex Othello Strategies Through Evolutionary Neural Networks 1995
David E. Moriarty and Risto Miikkulainen, Connection Science, Vol. 7 (1995), pp. 195--209.
Laterally Interconnected Self-Organizing Feature Map In Handwritten Digit Recognition 1995
Yoonsuck Choe, Masters Thesis, Department of Computer Sciences, The University of Texas at Austin. 65. Technical Report AI95-236.
Learning Sequential Decision Tasks 1995
David E. Moriarty and Risto Miikkulainen, Technical Report AI95-229, Department of Computer Sciences, The University of Texas at Austin.
Modeling Cortical Plasticity Based On Adapting Lateral Interaction 1995
Joseph Sirosh and Risto Miikkulainen, In The Neurobiology of Computation: {T}he Proceedings of the Third Annual Computation and Neural Systems Conference, James M. Bower (Eds.), pp. 305-310 1995.
Ocular Dominance and Patterned Lateral Connections in a Self-Organizing Model of the Primary Visual Cortex 1995
Joseph Sirosh and Risto Miikkulainen, In Advances in Neural Information Processing Systems 7, Gerald Tesauro and David S. Touretzky and Todd K. Leen (Eds.), pp. 109-116 1995. Cambridge, MA: MIT Press.
SARDNET: A Self-Organizing Feature Map For Sequences 1995
Daniel L. James and Risto Miikkulainen, In Advances in Neural Information Processing Systems 7 (NIPS'94), G. Tesauro, D. S. Touretzky, and T. K. Leen (Eds.), pp. 577--584, Denver, CO 1995. Cambridge, MA: MIT Press.
Script-Based Inference And Memory Retrieval In Subsymbolic Story Processing 1995
Risto Miikkulainen, Applied Intelligence (1995), pp. 137-163.
Visual Schemas In Object Recognition And Scene Analysis 1995
Risto Miikkulainen and Wee Kheng Leow, In The Handbook of Brain Theory and Neural Networks, M. A. Arbib (Eds.), pp. 1029--1031, Cambridge, MA 1995. MIT Press.
Visualizing High-Dimensional Structure with the Incremental Grid Growing Network 1995
Justine Blackmore, Masters Thesis, Department of Computer Sciences, The University of Texas at Austin. Technical Report AI95-238.
Visualizing High-Dimensional Structure With The Incremental Grid Growing Neural Network 1995
Justine Blackmore and Risto Miikkulainen, In Machine Learning: Proceedings of the 12th Annual Conference, Armand Prieditis and Stuart Russell (Eds.), pp. 55-63, Austin, TX 1995. San Francisco, CA: Morgan Kaufmann. 55-63. Technical Repo...
A Connectionist Corpus-Based Approach to the Building of Word Representations 1994
Rupert L. Tang, Technical Report HR-94-01, Department of Computer Science, The University of Texas at Austin.
Cooperative Self-Organization Of Afferent And Lateral Connections In Cortical Maps 1994
Joseph Sirosh and Risto Miikkulainen, Biological Cybernetics (1994), pp. 66-78.
Evolutionary Neural Networks For Value Ordering In Constraint Satisfaction Problems 1994
David E. Moriarty and Risto Miikkulainen, Technical Report AI94-218, Department of Computer Sciences, The University of Texas at Austin.
Evolving Neural Networks To Focus Minimax Search 1994
David E. Moriarty and Risto Miikkulainen, In Proceedings of the Twelfth National Conference on Artificial Intelligence (AAAI-94), pp. 1371-1377, Seattle, WA 1994. Cambridge, MA: MIT Press.
Grounding Robotic Control With Genetic Neural Networks 1994
Diane Law and Risto Miikkulainen, Technical Report AI94-223, Department of Computer Sciences, The University of Texas at Austin.
Integrated Connectionist Models: Building AI Systems on Subsymbolic Foundations 1994
Risto Miikkulainen, Artificial Intelligence and Neural Networks: Steps Toward Principled IntegrationHonavar, V., and Uhr, L. (Eds.) (1994), pp. 483--508.
Lexical Disambiguation Based on Distributed Representations of Context Frequency 1994
Marshall R. Mayberry III and Risto Miikkulainen, In Proceedings of the 16th Annual Conference of the Cognitive Science Society, Ashwin Ram and Kurt Eiselt (Eds.), pp. 601-606 1994. Hillsdale, NJ: Erlbaum.
Priming, Perceptual Reversal, And Circular Reaction In A Neural Network Model Of Schema-Based Vision 1994
Wee Kheng Leow and Risto Miikkulainen, In Proceedings of the 16th Annual Conference of the Cognitive Science Society, Ashwin Ram and Kurt Eiselt (Eds.), pp. 560-565 1994. Hillsdale, NJ: Erlbaum.
Representing And Learning Visual Schemas In Neural Networks For Scene Analysis 1994
Wee Kheng Leow and Risto Miikkulainen, In Proceedings of the Workshop on Neural Architectures and Distributed {AI}: {F}rom Schema Assemblages to Neural Networks, pp. 35-40, Los Angeles 1994. Center for Neural Engineering, Universit...
Searle, Subsymbolic Functionalism And Synthetic Intelligence 1994
Diane Law, Technical Report, Department of Computer Sciences, The University of Texas at Austin. Technical Report AI94-222.
Self-Organizing Feature Maps With Lateral Connections: Modeling Ocular Dominance 1994
Joseph Sirosh and Risto Miikkulainen, In Proceedings of the 1993 Connectionist Models Summer School, M. C. Mozer and P. Smolensky and D. S. Touretzky and J. L. Elman and A. S. Weigend (Eds.), pp. 31-38 1994.
The Capacity Of Convergence-Zone Episodic Memory 1994
Mark Moll, Risto Miikkulainen, Jonathan Abbey, In Proceedings of the Twelfth National Conference on Artificial Intelligence (AAAI-94), pp. 68-73, Seattle, WA 1994. Cambridge, MA: MIT Press.
Verb Inflections in German Child Language: A Connectionist Account 1994
Gert Westermann and Risto Miikkulainen, In Proceedings of the 16th Annual Conference of the Cognitive Science Society, Ashwin Ram and Kurt Eiselt (Eds.), pp. 928-933 1994. Hillsdale, NJ: Erlbaum.
VISOR: Learning Visual Schemas In Neural Networks For Object Recognition And Scene Analysis 1994
Wee Kheng Leow, PhD Thesis, Department of Computer Sciences, The University of Texas at Austin. 198 pages. Technical Report AI-94-219.
VISOR: Schema-Based Scene Analysis With Structured Neural Networks 1994
Wee Kheng Leow and Risto Miikkulainen, Neural Processing Letters, Vol. 1 (1994), pp. 18--23.
How Lateral Interaction Develops In A Self-Organizing Feature Map 1993
Joseph Sirosh and Risto Miikkulainen, In Proceedings of the IEEE International Conference on Neural Networks (San Francisco, CA), pp. 1360-1365 1993. Piscataway, NJ: IEEE.
Incremental Grid Growing: Encoding High-Dimensional Structure Into A Two-Dimensional Feature Map 1993
Justine Blackmore and Risto Miikkulainen, In Proceedings of the IEEE International Conference on Neural Networks (San Francisco, CA), pp. 450-455 1993. Piscataway, NJ: IEEE.
Multi-Level Neural Network Language Translator 1993
James A. Bednar, Technical Report HR-93-01, Department of Computer Sciences, The University of Texas at Austin.
Representing Visual Schemas in Neural Networks for Scene Analysis 1993
Wee Kheng Leow and Risto Miikkulainen, In Proceedings of the IEEE Conference on Neural Networks (ICNN-93), pp. 1612-1617, San Francisco, CA 1993. Piscataway, NJ: IEEE.
Subsymbolic Natural Language Processing: An Integrated Model Of Scripts, Lexicon, And Memory 1993
Risto Miikkulainen, , MIT Press, Cambridge, MA 1993. MIT Press.
Data Rectification Using Recurrent (Elman) Neural Networks 1992
Thomas W. Karjala, David M. Himmelblau and Risto Miikkulainen, In Proceedings of the International Joint Conference on Neural Networks (IJCNN-92), Vol. II, pp. 901--906, Baltimore, MD 1992. Piscataway, NJ: IEEE.
Trace Feature Map: A Model Of Episodic Associative Memory 1992
Risto Miikkulainen, Biological Cybernetics, Vol. 66 (1992), pp. 273--282.
A Neural Network For Attentional Spotlight 1991
Wee Kheng Leow and Risto Miikkulainen, In Proceedings of the International Joint Conference on Neural Networks (Singapore), AI91-165, pp. 436-441 1991. Piscataway, NJ: IEEE.
Evolving Finite State Behavior using Marker-Based Genetic Encoding of Neural Networks 1991
Brad Fullmer, Technical Report HR-91-01, Department of Computer Science, The University of Texas at Austin.
Natural Language Processing With Modular PDP Networks And Distributed Lexicon 1991
Risto Miikkulainen and Michael G. Dyer, Cognitive Science, Vol. 15 (1991), pp. 343-399.
Self-Organizing Process Based On Lateral Inhibition And Synaptic Resource Redistribution 1991
Risto Miikkulainen, In Proceedings of the 1991 International Conference on Artificial Neural Networks, Teuvo Kohonen and Kai M{"a}kisara and Olli Simula and Jari Kangas (Eds.), pp. 415-420 1991. Amsterdam: North-H...
Using Marker-Based Genetic Encoding Of Neural Networks To Evolve Finite-State Behaviour 1991
Brad Fullmer and Risto Miikkulainen, In Toward a Practice of Autonomous Systems: {P}roceedings of the First {E}uropean Conference on Artificial Life, Francisco J. Varela and Paul Bourgine (Eds.), pp. 255-262, Cambridge, MA 1991. ...
A PDP Architecture For Processing Sentences With Relative Clauses 1990
Risto Miikkulainen, In Proceedings of the 13th International Conference on Computational Linguistics (COLING-90), pp. 201--206, Helsinki, Finland: Yliopistopaino 1990.
DISCERN: A Distributed Artificial Neural Network Model Of Script Processing And Memory 1990
Risto Miikkulainen, PhD Thesis, University of California. 334.
Script Recognition With Hierarchical Feature Maps 1990
Risto Miikkulainen, Connection Science, Vol. 2 (1990), pp. 83-101.
     [Expand to show all 83][Minimize]
The OpenNERO AI Research and Education Platform 2009 - Present
Coevolution of Competitive and Cooperative Agent Behavior 2009 - Present
Neuroevolution in Real Time Games 2005 - Present
A computational analysis of meditation 2005 - Present
Learning Navigation for Personal Satellite Assistant using Neuroevolution 2004 - Present
Neural Network Models of Schizophrenic Language 2003 - Present
PGLISSOM: Perceptual Grouping in a Self-Organizing Map of Spiking Neurons 1999 - Present
Forming Text Representations with Neural Networks 1998 - Present
The Role of Emotion and Communication in Cooperative Behavior 2013 - 2016
Learning Strategic Behavior in Sequential Decision Tasks 2009 - 2014
A Predictive Simulation Model of Competitive Dynamics in Innovation 2009 - 2013
Borg: A General-Purpose Algorithm Portfolio System 2009 - 2013
Human-like Bots in Unreal Tournament 2008 - 2012
Modular Neuroevolution for Multilegged Locomotion 2007 - 2012
Evolving Controllers for Physical Multilegged Robots 2010 - 2011
Computational and Behavioral Evidence for Bilingual Aphasia Rehabilitation 2008 - 2011
NEAT: Evolving Increasingly Complex Neural Network Topologies 2000 - 2011
Constructing Intelligent Agents in Simulated Worlds 2008 - 2010
Leveraging Human Creativity with Machine Discovery 2008 - 2010
Evolving Locomotion Controllers for Multilegged Robots 2008 - 2010
Utilizing Symmetry in Evolutionary Design 2007 - 2010
NERO: NeuroEvolving Robotic Operatives 2003 - 2009
Computational Maps in the Visual Cortex 1987 - 2009
Trichromatic LISSOM 2005 - 2007
Leveraging Evolvability in Search 2004 - 2007
SODA: Self-Organizing Distinctive State Abstraction 2003 - 2007
Diverse Behavior in Teams of Homogeneous Agents 2001 - 2007
Cooperative Coevolution of Multi-Agent Systems 2000 - 2007
Learning Schemas for Robot Perception 2000 - 2007
NEAT: Evolving Vehicle Warning Systems 2004 - 2006
Developing Complex Systems Using Evolved Pattern Generators 2004 - 2006
Combining Rule-Based Knowledge with NEAT 2004 - 2006
Solving Non-Markov Control Tasks 1996 - 2006
Prenatal development of ocular dominance and orientation maps in a self-organizing model of V1 2004 - 2005
Evolving Neural Network Ensembles with NEAT 2004 - 2005
CLA: The Constructivist Learning Architecture 1998 - 2004
Controlling a Finless Rocket Through Neuroevolution 2002 - 2003
Refinement and On-Line Adaptation of Neurocontrollers Through Particle swarming 2001 - 2002
Nonlinear, Adaptive Process Control 2001 - 2002
Dynamic Resource Allocation on a Multiprocessor Chip 2000 - 2002
Sound System Differentiation Through Time 2000 - 2002
Evolving Confident Neural Networks 2000 - 2002
Self-Organization of Directional Selectivity 1999 - 2002
Optimizing a Manufacturing Process 1998 - 2002
Segmentation and Binding: the SLISSOM Model 1998 - 2002
Semantic Effect on Episodic Associations 1998 - 2002
Eugenic Evolution: The EuA, EuSANE, and TEAM 1998 - 2002
Self-Organization Driven by Internally-Generated Patterns 1997 - 2002
Creating Melodies with Evolving Recurrent Networks 2000 - 2001
GLISSOM: Modeling Large Cortical Maps 1999 - 2001
Modeling the Emergence of Syllable Systems 1998 - 2001
Understanding Complex Sentences with the Sentence Gestalt Model 1998 - 2001
Playing Go 1998 - 2001
Natural Deduction 1999 - 2000
Utilizing Population Culture in Neuroevolution 1998 - 2000
Adaptive Packet Routing: The Confidence-Based Dual Reinforcement Q-Learning Algorithm 1998 - 2000
Tilt Aftereffects in the RF-LISSOM Model 1996 - 2000
Orientation Perception in the RF-LISSOM Model 1995 - 2000
Structure and Capacity of Hippocampal Memory: The Convergence-Zone model 1994 - 2000
Subsymbolic Parsing of Sequences: The SARDSRN model 1998 - 1999
Real-time Interactive Gaming 1997 - 1999
Organization and Disorders of the Mental Lexicon: The DISLEX System 1990 - 1999
Intrusion Detection 1998 - 1998
Semantic Disambiguation in Sentence Processing 1994 - 1998
Realtime Continuous Adaptive Behavior: The Rodney System 1997 - 1997
Self-Organization in the Primary Visual Cortex: The RF-LISSOM Model 1995 - 1997
Controlling Chaos 1995 - 1997
Vision-Driven Development of Auditory Spatial Maps 1995 - 1997
On-Line Adaptation of a Signal Predistorter through Dual Reinforcement Learning 1995 - 1997
Symbiotic Evolution: The SANE System 1994 - 1997
Robot Control 1994 - 1997
Playing Othello 1994 - 1997
Schema-Based Object Recognition and Scene Analysis: The VISOR System 1993 - 1997
LISSOM: Laterally Interconnected Self-Organizing Maps 1987 - 1997
IGG: Visualization with Incremental Grid Growing 1993 - 1995
Marker-Based Encoding of Neural Networks 1991 - 1995
SARDNET: Forming Maps of Sequences 1994 - 1994
Understanding Sentences with Relative Clauses: The SPEC System 1993 - 1994
Processing Script-Based Stories: The DISCERN System 1990 - 1994
Storing Information on Maps: The Trace Feature Map Model 1990 - 1994
HFM: Hierarchical Features Maps 1989 - 1994
Learning Word Meanings: The FGREP Method 1987 - 1994
Data Rectification for Process Control 1992 - 1992
     [Expand to show all 32][Minimize]
Adapting Morphology to Multiple Tasks in Evolved Virtual CreaturesDan Lessin, Don Fussell, Risto Miikkulainen2014
Multimodal Behavior in Imprison Ms. Pac-ManJacob Schrum2014
Multimodal Behavior in Multiple Lives Ms. Pac-ManJacob Schrum2014
Multimodal Behavior in One Life Ms. Pac-ManJacob Schrum2014
Trading Control Intelligence for Physical Intelligence: Muscle Drives in Evolved Virtual CreaturesDan Lessin, Don Fussell, Risto Miikkulainen2014
A Neuroevolution Approach to General Atari Game PlayingMatthew Hausknecht2013
Open-Ended Behavioral Complexity for Evolved Virtual CreaturesDan Lessin, Don Fussell, Risto Miikkulainen2013
Cooperation to Overcome a More Powerful AdversaryKay Holekamp2012
Egalitarian Social Learning (ESL) in Robot ForagingWesley Tansey2012
Evolution of a Communication Code in Cooperative TasksAditya Rawal, Padmini Rajagopalan, Risto Miikkulainen, Kay Holekamp2012
Simulation of Competitive Multi-Agent Search on NK Fitness LandscapesErkin Bahceci2012
UT^2: Winner of 2012 BotPrize in Unreal Tournament 2004Jacob Schrum, Igor Karpov2012
Evolving Controllers for Physical Multilegged RobotsVinod Valsalam2011
Model-Based Visualization of Solver Performance DataBryan Silverthorn2011
Multi-modal Approaches to Evolving Behavior for Multi-task GamesJacob Schrum2011
The Role of Reward Structure, Coordination Mechanism and Net Return in the Evolution of CooperationPadmini Rajagopalan, Aditya Rawal2011
A Subsymbolic Model of Schizophrenic LanguageUli Grasemann2010
Emergence of Competitive and Cooperative Behavior and Arms Race Through CoevolutionAditya Rawal, Padmini Rajagopalan2010
Evolving Controller Symmetry for Multilegged RobotsVinod Valsalam2010
Fitness-based Shaping in Multi-objective DomainsJacob Schrum2010
Learning in Fractured DomainsNate Kohl2009
Multi-modal Behavior in NPCsJacob Schrum2009
Modular Neuroevolution for Multilegged LocomotionVinod Valsalam2008
Multi-objective Neuroevolution of NPCsJacob Schrum2008
Evolving Cooperation in Multiagent SystemsChern Yong2007
Handwritten Digit Recognition Utilizing Evolved Pattern GeneratorsVinod Valsalam2007
Neuro-Evolving Robotic Operatives (NERO)Kenneth Stanley2007
Adaptive Teams of Agents in the Legion II gameBobby Bryant2006
Evolving Vehicle Warning SystemsNate Kohl2006
Finless Rocket ControlFaustino Gomez2003
Neuroevolution of Augmenting Topologies DemosKenneth Stanley2003
Double Pole Balancing with ESPFaustino Gomez1999
     [Expand to show all 41][Minimize]
MM-NEAT Modular Multiobjective NEAT is a software framework in Java that builds on the basic principles of 2014

MARLEDA Markovian Learning Estimation of Distribution Algorithm (MARLEDA) is an Estimation of Distribution Algorithm (EDA) that ... 2013

mMARLEDA The mMarleda package extends the MARLEDA software to multiobjective optim... 2013

ESL This is the C# source code for the experiments with Egalitarian Social Learning (ESL) in a robot foraging domain. The re... 2012

UT^2: Winning Botprize 2012 Entry The Botprize Competition is an annual competition to program bots that appear human-l... 2012

Borg

The borg project includes a practical algorithm...

2011

NKVis This package contains a 3D visualization tool for NK fitness landscapes. Two types of visualizations are provided: a 2011

PyEC Python package containing source code for Evolutionary Annealing along with a number of other evolutionary and stochasti... 2011

BREVE Monsters BREVE is a system for designing Artificial Life simulations available at http://spiderlan... 2010

ENSO This package contains software implementing the ENSO approach for evolving symmetric modular neural networks. It also in... 2010

NEAT C++ The NEAT package contains source code implementing the NeuroEvolution of Augmenting Topologies method. The source code i... 2010

OpenNERO OpenNERO is a general research and education platform for artificial intelligence. The platform is based on a simulatio... 2010

Sorting Networks This package contains software utilizing an approach based on symmetry and evolution to minimize the number of comparato... 2010

Austin Arboretum Foliage Corpus Photographs for use with color modeling work taken by Judah De Paula at the Austin Arboretum. Images contain mostly leav... 2007

De Paula dissertation support files The trichromatic LISSOM simulations and support scripts used to generate the data presented in the De Paula dissertation... 2007

Flowers Color Image Corpus Photographs for use with color modeling work taken by Judah De Paula at the Austin Arboretum. Images contain mostly clos... 2007

RGBtoLMS Python code to convert RGB images to simulated Long, Medium, and Short photoreceptor cone activations. The program also... 2007

rtNEAT C++ The rtNEAT package contains source code implementing the real-time NeuroEvolution of Augmenting Topologies method. In ad... 2006

NEAT: ANJI (Another NEAT Java Implementation) The ANJI package contains Java source code for the NeuroEvolution of Augmenting Topologies method (see the original 2004

NEAT C# The SharpNEAT package contains C# source code for the NeuroEvolution of Augmenting Topologies method (see the original <... 2003

NEAT Delphi The Delphi NEAT package contains Delphi source code for the NeuroEvolution of Augmenting Topologies method (see the orig... 2003

NEAT Matlab The Matlab NEAT package contains Matlab source code for the NeuroEvolution of Augmenting Topologies method (see the orig... 2003

ESP JAVA 1.1 The ESP package contains the source code for the Enforced Sup-Populations system written in Java. This package is a near... 2002

NEAT C++ for Microsoft Windows The Windows NEAT package contains C++ source code for the NeuroEvolution of Augmenting Topologies method (see the origin... 2002

NEAT Java (JNEAT) The JNEAT package contains Java source code for the NeuroEvolution of Augmenting Topologies method (see the original 2002

PGLISSOM This package is a simulator for the PGLISSOM model of perceptual grouping and self-organization in the visual cortex. Th... 2002

SignalSim The SignalSim Spiking Neuron package is a Tcl/Tk GUI built on top of an event-driven simulator of an interconnected net... 2002

SOFM The SOFM package contains C- and TK/TCL-code (integrated through SWIG) for the standard feature map algorithm for formi... 2002

TEAM The TEAM package contains C++ implementations of both EuA (The Eugenic Algorithm) and TEAM (The Eugenic Algorithm with M... 2002

LISSOM

The LISSOM package contains the C++, Python, and Scheme source code and examples for training and testing firing-rate...

2001

ESP C++ The ESP package contains the source code for the Enforced Sup-Populations system written in C++. ESP is an extension t... 2000

JavaSANE The JavaSANE package contains the source code for the Hierarchical SANE system, based on SANE-C, but rewritten extensive... 1998

MIR Sentence Processing Package The MIR Sentence Processing package contains the C source code for the MIR system, as well as a selection of scripts wi... 1998

SANE-C The SANE-C package contains the source code for the Hierarchical SANE system, written in C. This package has been rewrit... 1997

Polebalancing This simulator contains the code used to compare (neuron-level) SANE to one- and two-layer adaptive heuristic critics in... 1995

DISLEX

This package contains the C-code and data for training and testing the DISLEX model of the lexicon, which is also par...

1994

FGREPNET The FGREPNET package contains the C-code and data for training and testing an FGREP network in developing distributed re... 1994

HFM The HFM package contains the C-code and data for training and testing the HFM memory organization and hierarchical class... 1994

PROC The PROC package contains the C-code and data for training and testing the story processing modules of the DISCERN syste... 1994

SPEC The SPEC package contains the C-code and data for training and testing the SPEC system for processing complex sentences ... 1994

DISCERN DISCERN is a large, modular neural network system for reading, paraphrasing and answering questions about stereotypical ... 1993