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Titlebook: Optimization, Control, and Applications of Stochastic Systems; In Honor of Onésimo Daniel Hernández-Hernández,J. Adolfo Minjárez-Sosa Book

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On the Regularity Property of Semi-Markov Processes with Borel State Spaces,ched with probability one for every initial state; (c) it has a unique invariant probability measure. Under the latter condition, the regularity property is only ensured for almost all initial states with respect to the invariant probability measure.
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Book 2012e of applications of stochastic control and some of its recent theoretical developments. These topics include various aspects of dynamic programming, approximation algorithms, and infinite-dimensional linear programming. In all, the work comprises 18 carefully selected papers written by experts in t
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A Constrained Optimization Problem with Applications to Constrained MDPs,d-optimal policies and characterize a constrained-optimal policy without the nonnegativity assumption on the costs as in the previous literature. Furthermore, we apply our results to discrete-time constrained MDPs with . discount factors.
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Approximation of Infinite Horizon Discounted Cost Markov Decision Processes,unction. Based on Lipschitz continuity of the elements of the control model, we propose a state and action discretization procedure for approximating the optimal value function and an optimal policy of the original control model. We provide explicit bounds on the approximation errors.
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Continuous-Time Controlled Jump Markov Processes on the Finite Horizon,e solution of the corresponding dynamic programming equation. This leads to the existence of an optimal Markov control. We then consider a zero-sum game. We show that the value function exists and is the unique solution of the corresponding Isaacs equations. This yields the existence of a pair of saddle point Markov strategies.
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Optimal Execution of Derivatives: A Taylor Expansion Approach,m. To do so, we first use a Taylor expansion of the derivative with respect to the price of the underlying asset at time zero. We then use up to the second-order approximation to solve the mean-variance optimization problem.
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Estimation of the Optimality Deviation in Discounted Semi-Markov Control Models,uming that the holding times distribution. is unknown, but it is possible to get an approximate distribution., such optimality deviation measures the quality of this approximation according if an optimal policy for the control model corresponding to. is still good for the original one determined for..
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Optimization, Control, and Applications of Stochastic Systems978-0-8176-8337-5Series ISSN 2324-9749 Series E-ISSN 2324-9757
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