Results in Control and Optimization, 2022 This paper proposes an optimistic value iteration for steady-state mean–variance optimization in infinite-horizon discounted Markov decision processes (MDPs). The involved variance metric concerns reward variability in the long run, and future deviations
Shuai Ma, Xiaoteng Ma, Li Xia
doaj
Optimal treatment recommendations for diabetes patients using the Markov decision process along with the South Korean electronic health records. [PDF]
Sci Rep, 2021 Oh SH, Lee SJ, Noh J, Mo J.
europepmc +1 more source
Contralateral exploration and repair of occult inguinal hernias during laparoscopic inguinal hernia repair: systematic review and Markov decision process. [PDF]
BJS Open, 2021 Dhanani NH +7 more
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Steady state availability general equations of decision and sequential processes in Continuous Time Markov Chain models [PDF]
arXiv, 2017 Continuous Time Markov Chain (CMTC) is widely used to describe and analyze systems in several knowledge areas. Steady state availability is one important analysis that can be made through Markov chain formalism that allows researchers generate equations for several purposes, such as channel capacity estimation in wireless networks as well as system ...
arxiv
The existence of optimal control for continuous-time Markov decision processes in random environments [PDF]
arXiv, 2019 In this work, we investigate the optimal control problem for continuous-time Markov decision processes with the random impact of the environment. We provide conditions to show the existence of optimal controls under finite-horizon criteria. Under appropriate conditions, the value function is continuous and satisfies the dynamic programming principle ...
arxiv
Algebraic Markov Decision Processes [PDF]
, 2005 In this paper, we provide an algebraic approach to Markov Decision Processes (MDPs), which allows a unified treatment of MDPs and includes many existing models (quantitative or qualitative) as particular cases. In algebraic MDPs, rewards are expressed in a semiring structure, uncertainty is represented by a decomposable plausibility measure valued on a
Perny, Patrice +2 more
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On gradual-impulse control of continuous-time Markov decision processes with multiplicative cost
, 2018 In this paper, we consider the gradual-impulse control problem of continuous-time Markov decision processes, where the system performance is measured by the expectation of the exponential utility of the total cost. We prove, under very general conditions
Guo, Xin +3 more
core
A Theory of Regularized Markov Decision Processes
, 2019 International ...
Geist, Matthieu +2 more
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Federated Learning with Efficient Aggregation via Markov Decision Process in Edge Networks
MathematicsFederated Learning (FL), as an emerging paradigm in distributed machine learning, has received extensive research attention. However, few works consider the impact of device mobility on the learning efficiency of FL.
Tongfei Liu, Hui Wang, Maode Ma
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