Markov Decision Processes with Finite Time Horizon In this section we consider Markov Decision Models with a finite time horizon. an interdisciplinary study, we should develop a comprehensible method for medical workers and doctors to optimize the supply chain, maintain the quality of services and overcome the challenges. Adapting Markov Decision Process for Search Result Diversification Long Xia, Jun Xu, Yanyan Lan, Jiafeng Guo, Wei Zeng, Xueqi Cheng CAS Key Lab of Network Data Science and Technology, Institute of Computing Technology, Chinese Academy of Sciences fxialong,zengweig@so›ware.ict.ac.cn,fjunxu,lanyanyan,guojiafeng,[email protected] ABSTRACT In this … /Filter /FlateDecode However, more observations of random information will lead to better decisions. recognition. First, for small scale problems the optimal admission and scheduling policy can be obtained with, e.g., policy iteration. for the open set was 88.2%, One-Step Improvement Ideas and Computational Aspects, Value Function Approximation in Complex Queueing Systems, Approximate Dynamic Programming by Practical Examples, Server Optimization of Infinite Queueing Systems, Structures of Optimal Policies in MDPs with Unbounded Jumps: The State of Our Art, Markov Decision Processes for Screening and Treatment of Chronic Diseases, Stratified Breast Cancer Follow-Up Using a Partially Observable MDP, Stochastic Dynamic Programming for Noise Load Management, Analysis of a Stochastic Lot Scheduling Problem with Strict Due-Dates, Near-Optimal Switching Strategies for a Tandem Queue, Wireless Channel Selection with Restless Bandits, Flexible Staffing for Call Centers with Non-stationary Arrival Rates, MDP for Query-Based Wireless Sensor Networks, Optimal Portfolios and Pricing of Financial Derivatives Under Proportional Transaction Costs, A simple empirical model for blood platelet production and inventory management under uncertainty, Task offloading in mobile fog computing by classification and regression tree, Modeling and Optimizing Resource Allocation Decisions through Multi-model Markov Decision Processes with Capacity Constraints, On computational procedures for Value Iteration in inventory control, Dynamic repositioning strategy in a bike-sharing system; how to prioritize and how to rebalance a bike station, Semi-additive functionals of semi-Markov processes and measure-valued Poisson equation, Risk-Averse Markov Decision Processes under Parameter Uncertainty with an Application to Slow-Onset Disaster Relief, Deep Influence Diagrams: An Interpretable and Robust Decision Support System, Mapping the uncertainty of 19th century West African slave origins using a Markov decision process model, Probabilistic life cycle cash flow forecasting with price uncertainty following a geometric Brownian motion, Risk Aversion to Parameter Uncertainty in Markov Decision Processes with an Application to Slow-Onset Disaster Relief, A Survey on the Computation Offloading Approaches in Mobile Edge/Cloud Computing Environment: A Stochastic-based Perspective, Non-myopic dynamic routing of electric taxis with battery swapping stations, Estimating conditional probabilities of historical migrations in the transatlantic slave trade using kriging and Markov decision process models, Autonomous computation offloading and auto-scaling the in the mobile fog computing: a deep reinforcement learning-based approach, An Overview for Markov Decision Processes in Queues and Networks, Optimizing dynamic switching between fixed and flexible transit services with an idle-vehicle relocation strategy and reductions in emissions, Efficiency and productivity for decision making on low-power heterogeneous CPU+GPU SoCs, Emotion Regulation as Risk Management for Industrial Crisis Resolution: An MDP model driven by field data on Interpersonal Emotion Management (IEM), Efficient Planning in Large MDPs with Weak Linear Function Approximation, Information Directed Policy Sampling for Partially Observable Markov Decision Processes with Parametric Uncertainty: Proceedings of the 2018 INFORMS International Conference on Service Science, ONLINE CAPACITY PLANNING FOR REHABILITATION TREATMENTS: AN APPROXIMATE DYNAMIC PROGRAMMING APPROACH, Finite-horizon piecewise deterministic Markov decision processes with unbounded transition rates, Finite horizon continuous-time Markov decision processes with mean and variance criteria, Optimizing Energy-Performance Trade-Offs in Solar-Powered Edge Devices, Strongly Polynomial Algorithms for Transient and Average-Cost MDPs, Dynamic urban traffic flow management using floating car, planning, and infrastructure data, PhD project at Jeroen Bosch Hospital (Den Bosch, NL). 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