Markov Decision Processes with Applications
A special issue of Mathematics (ISSN 2227-7390). This special issue belongs to the section "Probability and Statistics".
Deadline for manuscript submissions: 31 May 2024 | Viewed by 243
Special Issue Editors
Interests: bandit processes; markov decision processes; dynamic data science; financial time series
Interests: risk management; mathematical finance; dynamic pricing; Markov decision processes; response adaptive clinical trials (ethics, statistical design and analysis); sequential design of experiments; bandit processes; biostatistics; reinforcement learning
Special Issue Information
Dear Colleagues,
Markov decision process (MDP), also known as stochastic dynamic programming, is a mathematical framework for dynamic and sequential decision-making under stochastic uncertainty. MDPs have been investigated extensively and informed sequential decision-making in a variety of application areas including reinforcement learning, finance, inventory control, scheduling, and clinical trials, just to name a few. The purpose of this Special Issue is to collect and present some state-of-the-art developments in the theory, methodology and applications of MDPs.
Dr. You Liang
Prof. Dr. Xikui Wang
Guest Editors
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Mathematics is an international peer-reviewed open access semimonthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
Keywords
- Markov processes
- stochastic control
- dynamic programming
- decision making
- reinforcement learning
