Reinforcement Learning for Decision-Making in Intelligent Systems
A special issue of Applied System Innovation (ISSN 2571-5577).
Deadline for manuscript submissions: 20 January 2027 | Viewed by 109
Editors
Interests: reinforcement learning; scientific computing; bayesian inference; machine learning
Special Issue Information
Dear Colleagues,
Intelligent decision-making systems are becoming ubiquitous as both software and hardware are becoming more sophisticated. However, due to the large amount of data generated by modern systems, traditional decision-making approaches fail to function accordingly, since the state-spaces become too vast to allow for analytical analysis. Reinforcement learning is a machine learning approach that, unlike supervised/unsupervised learning, involves autonomous agents that, through sequential decision-making, learn optimal policies that allow them to navigate their environment by maximizing cumulative rewards.
This Special Issue aims to gather cutting-edge research papers in applied, scalable reinforcement learning for smart, autonomous decision-making of intelligent systems such as fleets of autonomous vehicles, energy systems, network optimization or other related areas. We welcome original research articles, review and survey papers and innovative case studies that focus on reinforcement learning algorithms, intelligent systems, autonomous decision-making, digital twins and smart manufacturing. Papers in other domains such as finance or medicine will also be considered.
This Special Issue provides a platform to researchers and practitioners to share their work and inform on the latest trends in the area of artificial intelligence applications in autonomous decision-making.
Dr. Erotokritos Skordilis
Dr. Zhiqiang 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 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-anonymized peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Applied System Innovation is an international peer-reviewed open access monthly 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 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.
Keywords
- reinforcement learning
- intelligent systems
- autonomous decision-making
- smart communities
- digital twins
- smart manufacturing
- autonomous vehicles
- energy systems
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