Aims

Mathematics (ISSN 2227-7390) is an international, open access journal which provides an advanced forum for studies related to mathematical sciences. It devotes exclusively to the publication of high-quality reviews, regular research papers and short communications in all areas of pure and applied mathematics. Mathematics also publishes timely and thorough survey articles on current trends, new theoretical techniques, novel ideas and new mathematical tools in different branches of mathematics. A submission must be well written and of interest to a substantial number of mathematicians and scientists.

Our aim is to encourage scientists to publish their experimental and theoretical results in as much detail as possible. There is no restriction on the maximum length of the papers. The full account of the research must be provided so that the results can be reproduced. Electronic files or software which provide the full details of the calculations, proofs and experimental procedures can be deposited as supplementary material (if unable to be published in a normal way).

Scope

Main topics include, but are not limited to the following:

    Algebraic geometry
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    Algorithms
    Analysis of PDEs
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    Variational problems

Special Issue on Algorithmic Advances in Reinforcement Learning: Theory and Applications
截稿日期: 2026-04-30

Special Issue Information

Dear Colleagues,

Reinforcement Learning (RL) has emerged as a powerful paradigm for sequential decision-making and optimization in complex, dynamic, and uncertain environments. In recent years, we have witnessed remarkable algorithmic advances that bridge theoretical foundations with diverse real-world applications such as robotics, healthcare, finance, and autonomous systems. Despite these developments, challenges remain around improving sample efficiency, ensuring stability, and establishing rigorous performance guarantees.

This Special Issue, ‘Algorithmic Advances in Reinforcement Learning: Theory and Applications’ (https://www.mdpi.com/si/258233), aims to bring together high-quality contributions that advance the state of the art in both theoretical and applied aspects of RL. We welcome submissions that address novel algorithms, convergence analysis, exploration–exploitation strategies, and hierarchical and multi-agent settings, as well as interdisciplinary applications. Both methodological papers and application-driven studies that include theoretical insights are encouraged.

We look forward to your valuable contributions, which will help to foster a deeper understanding of RL and its transformative potential across domains.

Dr. Yinglong Dai
Dr. Ke Li
Guest Editors


Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website (https://www.mdpi.com/user/login/). Once you are registered, click here to go to the submission form (https://susy.mdpi.com/user/manuscripts/upload/?journal=mathematics). 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 250 words) can be sent to the Editorial Office for assessment.

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:
reinforcement learning
algorithmic advances
theory and convergence
exploration and exploitation
hierarchical learning
multi-agent systems
real-world applications