ESP C++
Released 2000
The ESP package contains the source code for the Enforced Sup-Populations system written in C++. ESP is an extension to the SANE algorithm that segregates the neurons into sub-populations, one for each hidden unit in the networks being evolved. This allows neuron specializations to form more rapidly through constrained mating and enables the system to evolve recurrent networks. This package applies ESP to a non-Markov version of the double pole balancing problem. This is a difficult control task that requires short-term memory. For more details on ESP and/or the double pole system, see this paper on ESP or others found under Neuroevolution Methods and Applications.
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Faustino Gomez Postdoctoral Alumni tino [at] idsia ch
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IJCNN-2013 Tutorial on Evolution of Neural Networks 2013
Risto Miikkulainen, To Appear In unpublished. Tutorial slides..
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.
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.
Neuroevolution 2010
Risto Miikkulainen, In Encyclopedia of Machine Learning, New York 2010. Springer.
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.
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.
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.
Robust Non-Linear Control through Neuroevolution 2003
Faustino J. Gomez, PhD Thesis, Department of Computer Sciences, The University of Texas at Austin.
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)
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.
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.
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.
Incremental Evolution Of Complex General Behavior 1997
Faustino Gomez and Risto Miikkulainen, Adaptive Behavior, 5 (1997), pp. 317-342.