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Policy Gradient Methods for Reinforcement Learning with Function Approximation

, , , and . Advances in Neural Information Processing Systems, 12, page 1057--1063. The MIT Press, (2000)(Proceedings NIPS-99, Denver, Colorado, USA, November 29 - December 4, 1999).

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The shrinking generator, , and . CRYPTO '93: Proceedings of the 13th annual international cryptology conference on Advances in cryptology, page 22--39. New York, NY, USA, Springer-Verlag New York, Inc., (1994)Learning, Regret minimization, and Equilibria, and . Algorithmic Game Theory, chapter 4, Cambridge University Press, (2007)Policy Gradient Methods for Reinforcement Learning with Function Approximation, , , and . Advances in Neural Information Processing Systems, 12, page 1057--1063. The MIT Press, (2000)(Proceedings NIPS-99, Denver, Colorado, USA, November 29 - December 4, 1999).Policy Gradient Methods for Reinforcement Learning with Function Approximation, , , and . (2001)Mechanism Design via Machine Learning (short version), , , and . Proceedings of the 46th Foundations of Computer Science (FOCS 2005), page unknown. (2003)Convergence time to Nash equilibrium in load balancing, , and . (2007)Categorize arabic data sets using multi-class classification based on association rule approach., , , and . ISWSA, page 18. ACM, (2011)Image decomposition using independent component analysis., and . SIP, page 320-324. IASTED/ACTA Press, (2001)A New Intelligent Hybrid Feature Selection Method., and . AICCSA, page 1-6. IEEE Computer Society, (2018)Rule pruning and prediction methods for associative classification approach in data mining.. University of Huddersfield, UK, (2012)British Library, EThOS.