State-of-the-Art of Intelligent Decision Support Systems
A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Computing and Artificial Intelligence".
Deadline for manuscript submissions: 25 November 2025 | Viewed by 480
Special Issue Editors
Interests: artificial intelligence; fuzzy systems; intelligent decision-making; multi-agent systems; deep learning; machine learning
Interests: artificial intelligence; computational intelligence; machine learning; genetic/evolutionary algorithms; decision support theory; intelligent information systems; applications of hybrid intelligent information systems for modeling real world time series belonging to linear and non-linear systems; design and development of hybrid intelligent algorithms for solving timetabling and scheduling problems; multi-objective optimization
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
In the era of digital transformation, the confluence of advanced technologies has revolutionized the landscape of decision-making. The integration of artificial intelligence (AI) with Decision Support Systems (DSS) has given rise to Intelligent Decision Support Systems (IDSS) that are pivotal in navigating intricate, evolving, and ambiguous situations. These systems harness the power of sophisticated algorithms, including machine learning, robust classification, and role-based collaboration, to empower stakeholders with informed decision-making capabilities. The sophistication of neural networks and natural language processing techniques within IDSS has illuminated previously opaque data interdependencies, thereby enhancing the precision of decision-making outputs across industries such as healthcare, finance, and autonomous systems.
In light of these developments, we are pleased to announce the call for papers for this Special Issue which is dedicated to showcasing the forefront of research and practice in IDSS. Our focus is to delineate the breakthroughs in adaptive and intelligent decision-making, emphasizing the synergy between these advanced technologies and their applications. We invite researchers and practitioners to submit high-quality original research that delve into the themes outlined below.
Topics of interest include, but are not limited to, the following:
- information and knowledge engineering
- intelligent decision-making
- decision support systems
- multi-agent systems
- role-based collaboration
- machine learning
- robust classification
Dr. Libo Zhang
Prof. Dr. Grigorios Beligiannis
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. Applied Sciences 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 2400 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
- intelligent decision-making
- multi-agent systems
- intelligent collaboration
- machine learning
- robust classification
- information and knowledge engineering
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