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No Free Lunch Theorems for Optimization, and . Proceedings of the 1996 IEEE International Conference on Evolutionary Computation, 1, page 67--82. Piscataway, NJ: IEEE Computer Society Press, (April 1996)No Free Lunch Theorems for Optimization and Search, and . IEEE Transactions on Evolutionary Computation, (1997)Distributed Adaptive Control: Beyond Single-Instant, Discrete Control Variables., and . MSRAS, volume 28 of Advances in Soft Computing, page 31-52. Springer, (2004)Deep Reinforcement Learning for Event-Driven Multi-Agent Decision Processes., , , , , , and . CoRR, (2017)On the Bayesian” Occam factors” argument for Occam’s razor, and . Computational learning theory and natural learning systems III, T. Petsche et al.(eds), (1995)Bias Plus Variance Decomposition for Zero-One Loss Functions., and . ICML, page 275-283. Morgan Kaufmann, (1996)Collective Intelligence and Braess' Paradox., and . AAAI/IAAI, page 104-109. AAAI Press / The MIT Press, (2000)Bayesian Backpropagation Over I-O Functions Rather Than Weights.. NIPS, page 200-207. Morgan Kaufmann, (1993)Using Collective Intelligence to Route Internet Traffic., , and . NIPS, page 952-960. The MIT Press, (1998)Bayesian Optimization with a Finite Budget: An Approximate Dynamic Programming Approach., , and . NIPS, page 883-891. (2016)