Control
Control theory and engineering study how to produce the desired behavior in a variety of dynamical systems, e.g. the electro-mechanical systems in robots and the chemical systems in manufacturing plants. Such systems can be modeled mathematically in terms of state variables and how they change with respect to time and environmental conditions. The challenge is then to design the system component known as the controller such that the state variables change in desired and predictable ways. Our research in this area utilizes neural networks to implement controllers, and then optimizes those networks through learning and evolutionary algorithms. We have applied this approach to solve problems such as controlling the amount of thrust generated by rocket engines, regulating the complex biochemical processes in a bioreactor, and generating effective gaits for multilegged robots.
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IJCNN-2013 Tutorial on Evolution of Neural Networks Risto Miikkulainen To Appear In 2013. Tutorial slides.. 2013

General-Purpose Optimization Through Information-Maximization Alan J Lockett PhD Thesis, Department of Computer Sciences, The University of Texas at Austin, 2012. Tech Report AI... 2012

Constructing Controllers for Physical Multilegged Robots using the ENSO Neuroevolution Approach Vinod K. Valsalam, Jonathan Hiller, Robert MacCurdy, Hod Lipson and Risto Miikkulainen Evolutionary Intelligence, 5(1):1--12, 2012. 2012

Evolving Symmetry for Modular System Design Vinod K. Valsalam and Risto Miikkulainen IEEE Transactions on Evolutionary Computation, 15(3):368--386, 2011. 2011

Utilizing Symmetry and Evolutionary Search to Minimize Sorting Networks Vinod K. Valsalam and Risto Miikkulainen Technical Report AITR-11-09, Department of Computer Sciences, The University of Texas at Austin, Aus... 2011

Utilizing Symmetry in Evolutionary Design Vinod Valsalam PhD Thesis, Department of Computer Sciences, The University of Texas at Austin, Austin, TX, 2010. Te... 2010

Evolving Symmetric and Modular Neural Networks for Distributed Control Vinod K. Valsalam and Risto Miikkulainen In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO), 731--738, 200... 2009

Evolving Symmetric and Modular Neural Network Controllers for Multilegged Robots Vinod K. Valsalam and Risto Miikkulainen In xploring New Horizons in Evolutionary Design of Robots: Workshop at the 2009 IEEE/RSJ Internat... 2009

Accelerated Neural Evolution through Cooperatively Coevolved Synapses Faustino Gomez, Juergen Schmidhuber, and Risto Miikkulainen Journal of Machine Learning Research:937-965, 2008. 2008

Efficient Non-Linear Control through Neuroevolution Faustino Gomez, Juergen Schmidhuber, and Risto Miikkulainen In Proceedings of the European Conference on Machine Learning, 654-662, Berlin, 2006. Springe... 2006

Evolving Neural Network Ensembles for Control Problems David Pardoe, Michael Ryoo, and Risto Miikkulainen In Proceedings of the Genetic and Evolutionary Computation Conference, 2005. 2005

Transfer of Neuroevolved Controllers in Unstable Domains Faustino J. Gomez and Risto Miikkulainen In Proceedings of the Genetic and Evolutionary Computation Conference, Berlin, 2004. Springer... 2004

A Neurocontrol Paradigm for Intelligent Process Control using Evolutionary Reinforcement Learning Alex van Eck Conradie PhD Thesis, Department of Chemical Engineering, University of Stellenbosch, 2004. 2004

Robust Non-Linear Control through Neuroevolution Faustino J. Gomez PhD Thesis, Department of Computer Sciences, The University of Texas at Austin, 2003. 2003

Active Guidance for a Finless Rocket Using Neuroevolution Faustino J. Gomez and Risto Miikkulainen In Proceedings of the Genetic and Evolutionary Computation Conference, 2084-2095, San Francis... 2003

PhD Thesis: Robust Non-Linear Control through Neuroevolution Faustino J. Gomez Technical Report AI-TR-03-303, Department of Computer Sciences, University of Texas at Austin, Augus... 2003

Intelligent Process Control Utilizing Symbiotic Memetic Neuro-Evolution Alex v. E. Conradie, Risto Miikkulainen, and Christiaan Aldrich In Proceedings of the 2002 Congress on Evolutionary Computation, 6, 2002. 2002

Adaptive Control Utilising Neural Swarming Alex v. E. Conradie, Risto Miikkulainen, and Christiaan Aldrich In William B. Langdon and Erick Cantu-Paz and Keith E. Mathias and Rajkumar Roy and David Davis and... 2002

Alex van Eck Conradie Former Visitor
Faustino Gomez Postdoctoral Alumni tino [at] idsia ch
Aravind Gowrisankar Masters Alumni
Nate Kohl Ph.D. Alumni nate [at] natekohl net
Rini Sherony Former Collaborator rini sherony [at] tema toyota com
Jeremy Stober Ph.D. Student stober [at] cs utexas edu
Vinod Valsalam Ph.D. Alumni vkv [at] alumni utexas net
ENSO This package contains software implementing the ENSO approach for evolving symmetric modular neural networks. It also in... 2010