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    https://sophisticatedspectra.com/article/drosia-serenity-a-modern-oasis-in-the-heart-of-larnaca.2521391.html

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    Markov Decision Processes: Discrete Stochastic Dynamic Programming

    Posted By: AvaxGenius
    Markov Decision Processes: Discrete Stochastic Dynamic Programming

    Markov Decision Processes: Discrete Stochastic Dynamic Programming by Martin L. Puterman
    English | PDF | 1994 | 665 Pages | ISBN : 0471619779 | 27.35 MB

    The Wiley-Interscience Paperback Series consists of selected books that have been made more accessible to consumers in an effort to increase global appeal and general circulation. With these new unabridged softcover volumes, Wiley hopes to extend the lives of these works by making them available to future generations of statisticians, mathematicians, and scientists.

    Algorithms for Reinforcement Learning

    Posted By: AvaxGenius
    Algorithms for Reinforcement Learning

    Algorithms for Reinforcement Learning by Csaba Szepesvári
    English | PDF | 2010 | 103 Pages | ISBN : 1608454924 | 1.6 MB

    Reinforcement learning is a learning paradigm concerned with learning to control a system so as to maximize a numerical performance measure that expresses a long-term objective. What distinguishes reinforcement learning from supervised learning is that only partial feedback is given to the learner about the learner's predictions. Further, the predictions may have long term effects through influencing the future state of the controlled system. Thus, time plays a special role. The goal in reinforcement learning is to develop efficient learning algorithms, as well as to understand the algorithms' merits and limitations. Reinforcement learning is of great interest because of the large number of practical applications that it can be used to address, ranging from problems in artificial intelligence to operations research or control engineering. In this book, we focus on those algorithms of reinforcement learning that build on the powerful theory of dynamic programming. We give a fairly comprehensive catalog of learning problems, describe the core ideas, note a large number of state of the art algorithms, followed by the discussion of their theoretical properties and limitations.

    Probabilistic Graphical Models: Principles and Applications, Second Edition

    Posted By: AvaxGenius
    Probabilistic Graphical Models: Principles and Applications, Second Edition

    Probabilistic Graphical Models: Principles and Applications, Second Edition by Luis Enrique Sucar
    English | PDF | 2021 | 370 Pages | ISBN : 3030619427 | 11.7 MB

    This fully updated new edition of a uniquely accessible textbook/reference provides a general introduction to probabilistic graphical models (PGMs) from an engineering perspective. It features new material on partially observable Markov decision processes, graphical models, and deep learning, as well as an even greater number of exercises.

    Continuous-Time Markov Decision Processes: Borel Space Models and General Control Strategies

    Posted By: roxul
    Continuous-Time Markov Decision Processes: Borel Space Models and General Control Strategies

    Alexey Piunovskiy, "Continuous-Time Markov Decision Processes: Borel Space Models and General Control Strategies"
    English | ISBN: 3030549860 | 2020 | 608 pages | PDF | 6 MB

    Risk-Averse Capacity Control in Revenue Management

    Posted By: AvaxGenius
    Risk-Averse Capacity Control in Revenue Management

    Risk-Averse Capacity Control in Revenue Management by Christiane Barz
    English | PDF | 2007 | 167 Pages | ISBN : 3540730133 | 2.88 MB

    “If necessity is the mother of invention, then deregulation is the father, and r- enue management (also known as yield management) is the couple’s golden child – at least as far as operations research is concerned.” (Horner, 2000, p. 47) Deregulation had a signi?cant impact on the U.S. airline industry in the late 1970s.