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.
Alex van Eck Conradie Formerly affiliated Visitor
Faustino Gomez Postdoctoral Alumni tino [at] idsia ch
Aravind Gowrisankar Masters Alumni
Nate Kohl Ph.D. Alumni nate [at] natekohl net
Rini Sherony Formerly affiliated Collaborator rini sherony [at] tema toyota com
Jeremy Stober Ph.D. Student stober [at] cs utexas edu
Jeremy Stober Ph.D. Student stober [at] cs utexas edu
Vinod Valsalam Ph.D. Alumni vkv [at] alumni utexas net
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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.
IJCNN-2013 Tutorial on Evolution of Neural Networks 2013
Risto Miikkulainen, To Appear In unpublished. Tutorial slides..
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.
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.
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.
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.
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.
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.
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.
Accelerated Neural Evolution through Cooperatively Coevolved Synapses 2008
Faustino Gomez, Juergen Schmidhuber, and Risto Miikkulainen, Journal of Machine Learning Research (2008), pp. 937-965.
From pixels to policies: a bootstrapping agent 2008
Jeremy Stober and Benjamin Kuipers, In Proceedings of the IEEE International Conference on Development and Learning 2008.
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.
Parametrization and computations in shape spaces with area and boundary invariants 2006
Subramanian Ramamoorthy, Benjamin J. Kuipers and Lothar Wenzel, In Proc. Fall Workshop on Computational and Combinatorial Geometry, Northampton, MA 2006.
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.
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.
Controller synthesis using qualitative models and constraints 2004
Subramanian Ramamoorthy, Benjamin Kuipers, In Proceedings of the 18th International Workshop on Qualitative Reasoning, J. de Kleer and K. Forbus (Eds.), pp. 41--50 2004.
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.
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.
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.
Qualitative heterogeneous control of higher order systems 2003
Subramanian Ramamoorthy and Benjamin Kuipers, In Hybrid Systems: Computation and Control, Lecture Notes in Computer Science, O. Maler and A. Pnueli (Eds.) 2003. Springer Verlag.
Robust Non-Linear Control through Neuroevolution 2003
Faustino J. Gomez, PhD Thesis, Department of Computer Sciences, The University of Texas at Austin.
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...
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.
Qualitative modeling and heterogeneous control of global system behavior 2002
Benjamin Kuipers and Subramanian Ramamoorthy, In Hybrid Systems: Computation and Control, Lecture Notes in Computer Science, C. J. Tomlin and M. R. Greenstreet (Eds.) 2002. Springer Verlag.
Getting to the Airport: the Oldest Planning Problem in AI 2000
Vladimir Lifschitz, Norman McCain, Emilio Remolina and Armando Tacchella, In Logic-Based Artificial Intelligence, Jack Minker (Eds.), pp. 147-165 2000. Kluwer.
Missionaries and Cannibals in the Causal Calculator 2000
Vladimir Lifschitz, In Proceedings of International Conference on Principles of Knowledge Representation and Reasoning (KR), pp. 85-96 2000.
High-Speed Navigation with Approximate Maps 1995
Richard Froom, PhD Thesis, Department of Computer Sciences, The University of Texas at Austin.
The composition and validation of heterogeneous control laws 1994
Benjamin J. Kuipers and K. Astrom, Automatica, Vol. 30, 2 (1994), pp. 233--249.
Approximate maps for high-speed control of a mobile robot 1992
Richard Froom, In Mobile Robots VII: Proceedings of SPIE -- the International Society for Optical Engineering v. 1831, pp. 15--20, Boston, MA, November 1992.
Acquiring effective knowledge of environment geometry for minimum-time control of a mobile robot 1991
Richard Froom, In Proceedings of the 1991 IEEE International Symposium on Intelligent Control, pp. 501--506, Arlington, VA, August 1991.
The composition of heterogeneous control laws 1991
Benjamin Kuipers and Karl Astrom, In Proceedings of the American Control Conference, pp. 630--636 1991.
ENSO This package contains software implementing the ENSO approach for evolving symmetric modular neural networks. It also in... 2010