Algorithmic aspects of mean–variance optimization in Markov decision processes-Reference-Cited by-同舟云学术

Algorithmic aspects of mean–variance optimization in Markov decision processes

Published:2013-12 Issue:3 Volume:231 Page:645-653
ISSN:0377-2217
Container-title:European Journal of Operational Research
language:en
Short-container-title:European Journal of Operational Research

Author:

Mannor Shie,Tsitsiklis John N.

Publisher

Elsevier BV

Subject

Information Systems and Management,Management Science and Operations Research,Modeling and Simulation,General Computer Science,Industrial and Manufacturing Engineering

Reference29 articles.

1. Constrained Markov decision processes;Altman,1999

2. Arlotto, A., Gans, N., & Steel, M. J. (2013). Markov decision problems where means bound variances (Tech. Rep). .

3. Coherent measures of risk;Artzner;Mathematical Finance,1999

4. Bertsekas, D. (1995). Dynamic programming and optimal control. Athena Scientific.

5. Discounted MDP’s: Distribution functions and exponential utility maximization;Chung;SIAM Journal on Control and Optimization,1987

Cited by 20 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Dynamic Programming Principles for Mean-Field Controls with Learning;Operations Research;2023-07

2. Privacy-Preserving Reinforcement Learning Beyond Expectation;2022 IEEE 61st Conference on Decision and Control (CDC);2022-12-06

3. Risk-Sensitive Reinforcement Learning via Policy Gradient Search;Foundations and Trends® in Machine Learning;2022

4. Reinforcement Learning Beyond Expectation;2021 60th IEEE Conference on Decision and Control (CDC);2021-12-14

5. Robo-Advising: Enhancing Investment with Inverse Optimization and Deep Reinforcement Learning;2021 20th IEEE International Conference on Machine Learning and Applications (ICMLA);2021-12