Polynomial Time Algorithms for Branching Markov Decision Processes and Probabilistic Min(Max) Polynomial Bellman Equations-Reference-Cited by-同舟云学术

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Polynomial Time Algorithms for Branching Markov Decision Processes and Probabilistic Min(Max) Polynomial Bellman Equations

Published:2020-02 Issue:1 Volume:45 Page:34-62
ISSN:0364-765X
Container-title:Mathematics of Operations Research
language:en
Short-container-title:Mathematics of OR

Author:

Etessami Kousha¹^ORCID,Stewart Alistair²,Yannakakis Mihalis³

Affiliation:

1. School of Informatics, University of Edinburgh, Edinburgh EH8 9AB, United Kingdom;

2. Department of Computer Science, University of Southern California, Los Angeles, California 90089;

3. Department of Computer Science, Columbia University, New York, New York 10027

Publisher

Institute for Operations Research and the Management Sciences (INFORMS)

Subject

Management Science and Operations Research,Computer Science Applications,General Mathematics

Reference27 articles.

1. On the Complexity of Numerical Analysis

2. Approximating the Termination Value of One-Counter MDPs and Stochastic Games

3. Reachability in recursive Markov decision processes

4. The complexity of stochastic games

5. Markov decision processes and regular events

Cited by 3 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. A novel transfer deep learning model with reinforcement-learning-based hyperparameter optimization for short-term load forecasting during the COVID-19 pandemic;Journal of Intelligent & Fuzzy Systems;2022-07-21

2. Model-Free Reinforcement Learning for Branching Markov Decision Processes;Computer Aided Verification;2021

3. Qualitative Multi-objective Reachability for Ordered Branching MDPs;Lecture Notes in Computer Science;2020

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