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Min Max Control of Nonlinear Systems Using Universal Learning Networks.

, , , and . IJCNN (1), page 242-247. IEEE Computer Society, (2000)

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Function approximation using LVQ and fuzzy sets., , and . SMC, page 1442-1447. IEEE, (2001)Universal learning network and its application to robust control., , , and . IEEE Trans. Syst. Man Cybern. Part B, 30 (3): 419-430 (2000)Generalization Ability of Universal Learning Network by Optimizing Network Size and Time Delay., , , , and . ICONIP (1), page 371-374. Springer, (1997)A functions localized neural network with branch gates., , , and . Neural Networks, 16 (10): 1461-1481 (2003)Min Max Control of Nonlinear Systems Using Universal Learning Networks., , , and . IJCNN (1), page 242-247. IEEE Computer Society, (2000)Introduction and control of subgoals in reinforcement learning., , and . Artificial Intelligence and Applications, page 361-366. IASTED/ACTA Press, (2007)Universal Learning Networks with Branch Control., , , , and . IJCNN (3), page 97-102. IEEE Computer Society, (2000)0-7695-0619-4.Tackling Unit Commitment and Load Dispatch Problems Considering All Constraints with Evolutionary Computation., , and . CoRR, (2019)Curious: Searching for Unknown Regions of Space with a Subpopulation-based Algorithm., and . GECCO (Companion), page 145-146. ACM, (2016)A study on the importance of selection pressure and low dimensional weak learners to produce robust ensembles., , and . GECCO (Companion), page 1755-1756. ACM, (2013)