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The Convergence of a Cooperation Markov Decision Process System [PDF]
Entropy, 2020 In a general Markov decision progress system, only one agent’s learning evolution is considered. However, considering the learning evolution of a single agent in many problems has some limitations, more and more applications involve multi-agent.
Xiaoling Mo, Daoyun Xu, Zufeng Fu
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Improving RED algorithm congestion control by using the Markov decision process [PDF]
Scientific Reports, 2022 Congestion control plays an essential role on the internet to manage overload, which affects data transmission performance. The random early detection (RED) algorithm belongs to active queue management (AQM), which is used to manage internet traffic. The
Amar A. Mahawish, Hassan J. Hassan
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The Complexity of Markov Decision Processes [PDF]
Mathematics of Operations Research, 1987 We investigate the complexity of the classical problem of optimal policy computation in Markov decision processes. All three variants of the problem (finite horizon, infinite horizon discounted, and infinite horizon average cost) were known to be solvable in polynomial time by dynamic programming (finite horizon problems), linear programming, or ...
Christos H Papadimitriou
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Robust Markov Decision Processes [PDF]
Mathematics of Operations Research, 2013 Markov decision processes (MDPs) are powerful tools for decision making in uncertain dynamic environments. However, the solutions of MDPs are of limited practical use because of their sensitivity to distributional model parameters, which are typically unknown and have to be estimated by the decision maker.
Daniel Kuhn +2 more
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Data-Driven Markov Decision Process Approximations for Personalized Hypertension Treatment Planning [PDF]
MDM Policy & Practice, 2016 Background: Markov decision process (MDP) models are powerful tools. They enable the derivation of optimal treatment policies but may incur long computational times and generate decision rules that are challenging to interpret by physicians.
Greggory J. Schell PhD +4 more
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Multi-Vehicle Tracking via Real-Time Detection Probes and a Markov Decision Process Policy [PDF]
Sensors, 2019 Online multi-object tracking (MOT) has broad applications in time-critical video analysis scenarios such as advanced driver-assistance systems (ADASs) and autonomous driving.
Yi Zou +3 more
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Unusual Japanese Decision-making: Markov Process of Decision-making [PDF]
Revista de Management Comparat International, 2021 There is not enough research on decision-making and management process of organizations that do not make a profit. Economists should include healthy companies, as well as sick ones, the same way doctors do.
Nobumichi WATAHIKI +4 more
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Dialogue Strateqy Integrating Markov Decision Process and Information Entropy [PDF]
Jisuanji gongcheng, 2021 Dialogue strategy is an important component in the human-machine dialogue system,and its performance directly affects the performance of the dialogue system.In a cold start scenario without any data,it is complex and time-consuming to collect dialogue ...
ZHU Yingbo, ZHAO Yangyang, WANG Pei, YIN Kai, WANG Zhenyu
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Quantile Markov Decision Processes
Operations Research, 2022 Title: Sequential Decision Making Using Quantiles The goal of a traditional Markov decision process (MDP) is to maximize the expectation of cumulative reward over a finite or infinite horizon. In many applications, however, a decision maker may be interested in optimizing a specific quantile of the cumulative reward. For example, a physician may want
Xiaocheng Li +2 more
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Controllable Summarization with Constrained Markov Decision Process
Transactions of the Association for Computational Linguistics, 2021 We study controllable text summarization, which allows users to gain control on a particular attribute (e.g., length limit) of the generated summaries. In this work, we propose a novel training framework based on Constrained Markov Decision Process (CMDP)
Hou Pong Chan, Lu Wang, Irwin King
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