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This book presents state-of-the-art solution methods and applications of stochastic optimal control. It is a collection of extended papers discussed at the traditional Liverpool workshop on controlled stochastic processes with participants from both the east and the west. New problems are formulated, and progresses of ongoing research are reported. Topics covered in this book include theoretical results and numerical methods for Markov and semi-Markov decision processes, optimal stopping of Markov processes, stochastic games, problems with partial information, optimal filtering, robust control, Q-learning, and self-organizing algorithms. Real-life case studies and applications, e.g., queueing systems, forest management, control of water resources, marketing science, and healthcare, are presented. Scientific researchers and postgraduate students interested in stochastic optimal control,- as well as practitioners will find this book appealing and a valuable reference. .
Computational complexity. --- Engineering—Data processing. --- Computational intelligence. --- Statistical physics. --- Probabilities. --- Complexity. --- Data Engineering. --- Computational Intelligence. --- Applications of Nonlinear Dynamics and Chaos Theory. --- Probability Theory and Stochastic Processes. --- Probability --- Statistical inference --- Combinations --- Mathematics --- Chance --- Least squares --- Mathematical statistics --- Risk --- Physics --- Intelligence, Computational --- Artificial intelligence --- Soft computing --- Complexity, Computational --- Electronic data processing --- Machine theory --- Statistical methods --- Stochastic control theory. --- Control theory --- Stochastic processes --- Dynamics. --- Nonlinear theories. --- Engineering --- Nonlinear Optics. --- Stochastic analysis. --- Applied Dynamical Systems. --- Stochastic Analysis. --- Data processing. --- Analysis, Stochastic --- Mathematical analysis --- Optics, Nonlinear --- Optics --- Lasers --- Nonlinear problems --- Nonlinearity (Mathematics) --- Calculus --- Mathematical physics --- Dynamical systems --- Kinetics --- Mechanics, Analytic --- Force and energy --- Mechanics --- Statics
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This book offers a systematic and rigorous treatment of continuous-time Markov decision processes, covering both theory and possible applications to queueing systems, epidemiology, finance, and other fields. Unlike most books on the subject, much attention is paid to problems with functional constraints and the realizability of strategies. Three major methods of investigations are presented, based on dynamic programming, linear programming, and reduction to discrete-time problems. Although the main focus is on models with total (discounted or undiscounted) cost criteria, models with average cost criteria and with impulsive controls are also discussed in depth. The book is self-contained. A separate chapter is devoted to Markov pure jump processes and the appendices collect the requisite background on real analysis and applied probability. All the statements in the main text are proved in detail. Researchers and graduate students in applied probability, operational research, statistics and engineering will find this monograph interesting, useful and valuable. .
Probabilities. --- Statistics . --- System theory. --- Mathematical optimization. --- Probability Theory and Stochastic Processes. --- Statistics and Computing/Statistics Programs. --- Systems Theory, Control. --- Optimization. --- Optimization (Mathematics) --- Optimization techniques --- Optimization theory --- Systems optimization --- Mathematical analysis --- Maxima and minima --- Operations research --- Simulation methods --- System analysis --- Systems, Theory of --- Systems science --- Science --- Statistical analysis --- Statistical data --- Statistical methods --- Statistical science --- Mathematics --- Econometrics --- Probability --- Statistical inference --- Combinations --- Chance --- Least squares --- Mathematical statistics --- Risk --- Philosophy --- Markov processes. --- Discrete-time systems. --- DES (System analysis) --- Discrete event systems --- Sampled-data systems --- Digital control systems --- Discrete mathematics --- Linear time invariant systems --- Analysis, Markov --- Chains, Markov --- Markoff processes --- Markov analysis --- Markov chains --- Markov models --- Models, Markov --- Processes, Markov --- Stochastic processes --- Control theory. --- Probability Theory. --- Statistics and Computing. --- Systems Theory, Control . --- Data processing. --- Dynamics --- Machine theory
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Statistical science --- Numerical methods of optimisation --- Operational research. Game theory --- Probability theory --- waarschijnlijkheidstheorie --- statistiek --- systeemtheorie --- wiskunde
Choose an application
Choose an application
This book offers a systematic and rigorous treatment of continuous-time Markov decision processes, covering both theory and possible applications to queueing systems, epidemiology, finance, and other fields. Unlike most books on the subject, much attention is paid to problems with functional constraints and the realizability of strategies. Three major methods of investigations are presented, based on dynamic programming, linear programming, and reduction to discrete-time problems. Although the main focus is on models with total (discounted or undiscounted) cost criteria, models with average cost criteria and with impulsive controls are also discussed in depth. The book is self-contained. A separate chapter is devoted to Markov pure jump processes and the appendices collect the requisite background on real analysis and applied probability. All the statements in the main text are proved in detail. Researchers and graduate students in applied probability, operational research, statistics and engineering will find this monograph interesting, useful and valuable. .
Statistical science --- Numerical methods of optimisation --- Operational research. Game theory --- Probability theory --- waarschijnlijkheidstheorie --- statistiek --- systeemtheorie --- wiskunde
Choose an application
This book presents state-of-the-art solution methods and applications of stochastic optimal control. It is a collection of extended papers discussed at the traditional Liverpool workshop on controlled stochastic processes with participants from both the east and the west. New problems are formulated, and progresses of ongoing research are reported. Topics covered in this book include theoretical results and numerical methods for Markov and semi-Markov decision processes, optimal stopping of Markov processes, stochastic games, problems with partial information, optimal filtering, robust control, Q-learning, and self-organizing algorithms. Real-life case studies and applications, e.g., queueing systems, forest management, control of water resources, marketing science, and healthcare, are presented. Scientific researchers and postgraduate students interested in stochastic optimal control,- as well as practitioners will find this book appealing and a valuable reference. .
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