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  • Christopher Gatti
    978-3-319-12197-0
    2015
    Edition 1
    • Nominated by the Rensselaer Polytechnic Institute as an outstanding Ph.D. thesis
    • Explains reinforcement learning through a range of problems by exploring what affects reinforcement learning and what contributes to a successful implementation
    • Includes a contemporary design of experiments methods, comprising of a novel sequential experimentation procedure that finds convergent learning algorithm parameter subregions and stochastic kriging for response surface metamodeling
    • Includes supplementary material: sn.pub/extras
    €180 €162
    10% OFF

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