Incluye referencias bibliográficas e índice

Markov chain structure and models -- Historical note -- States and transitions -- Model of the weather -- Random walks -- Estimating transition probabilities -- Multiple-step transition probabilities -- State probabilities after multiple steps -- Classification of states -- Markov chain structure -- Markov chain models -- Regular Markov chains -- Steady-state probabilities -- First passage to a target state -- Reducible Markov chains -- Canonical form of the transition matrix -- The fundamental matrix -- Passage to a target state -- Eventual passage to a closed set within a reducible multichain -- Limiting transition probability matrix -- A Markov chain with rewards (MCR) -- Rewards -- Undiscounted rewards -- Discounted rewards -- A Markov decision process (MDP) -- An undiscounted MDP -- A discounted MDP -- Special topics : state reduction and Hidden Markov chains -- State reduction -- An introduction to hidden Markov chains

"This book presents an introduction to finite Markov chains and Markov decision processes, with applications in engineering and management. It introduces discrete-time, finite-state Markov chains, and Markov decision processes. The text describes both algorithms and applications, enabling students to understand the logical basis for the algorithms and be able to apply them. The applications address problems in government, business, and nonprofit sectors. The author uses Markov models to approximate the random behavior of complex systems in diverse areas, such as management, production, science, education, health services, finance, and marketing"-- Biblioteca del congreso

Fondos PIFI Compra 120912 0.00

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