Feature Paper Special Issue: Reinforcement Learning

Dear Colleagues,

Machine-learning methods can be classified into three general categories: unsupervised learning, supervised learning and reinforcement learning. Of the three, reinforcement learning holds the promise to create artificial intelligence that can surpass human capacity in specialized tasks such as gaming (e.g., Google AlphaGo, AlphaGo Zero, AlphaZero) or research (e.g., Google AlphaFold). 

Reinforcement learning spans diverse academic areas including statistics, operations research, computational mathematics and computer science. We are organizing this Special Issue to help promote the development of this research frontier, and we are honored to feature incoming papers from leaders in this field including Professor Richard Sutton, co-author of the first textbook [1] in this field, and Professor Jiaqiao Hu, co-developer of the Monte Carlo tree search algorithm [2] that lies behind the success of the Google AlphaGo. We welcome colleagues from all related fields to contribute to this Special Issue as authors and/or Guest Editors. Accepted papers will be published sequentially without delay and without publication fee, to help advance this important research topic.

[1] Sutton, Richard S.; Barto, Andrew G. (2018). Reinforcement Learning: An Introduction (2 ed.). MIT Press. ISBN 978-0-262-03924-6.

[2] Chang, Hyeong Soo; Fu, Michael C.; Hu, Jiaqiao; Marcus, Steven I. (2005). "An Adaptive Sampling Algorithm for Solving Markov Decision Processes". Operations Research. 53: 126–139.

Procedure

All submissions will be rigorously reviewed according to the Stats journal guidelines.

Authors of manuscripts that are not suitable for this Special Issue will be notified as soon as after consultation with the Editorial Board Members. Authors of these manuscripts may still consider submitting in other Special Issues or as a regular paper. Other manuscripts will be forwarded for review.

Manuscripts that are not selected as feature papers will be notified after the first round of reviews. The selection will be based on the review. Authors of those manuscripts that are not selected for the Special Issue may decide to revise and submit as a regular paper in Stats. Please note that authors of these manuscripts need to shoulder the publication fees.

Other manuscripts will be sent for a second round of reviews. However, this does not necessarily mean that a manuscript under the second round of reviews will be published as a feature paper. We will still seek comments and suggestions from reviewers.

Prof. Dr. Wei Zhu
Dr. Sourav Sen
Dr. Keli Xiao
Guest Editors

Manuscript Submission Information

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Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1600 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.

• reinforcement learning
• dynamic programming
• Markov decision process
• multi-agent system