Special Issue "Multi-Agent Systems Design, Analysis, and Applications"

A special issue of Algorithms (ISSN 1999-4893).

Deadline for manuscript submissions: 31 October 2020.

Special Issue Editors

Dr. Angelo Fanelli
Guest Editor
CNRS (Centre National de la Recherche Scientifique), UMR-6211, 14000 Caen, France
Interests: game theory; social choice; artificial intelligence; data science
Dr. Gianpiero Monaco
Guest Editor
Department of Information Engineering Computer Science and Mathematics, University of L'Aquila, 67100 Coppito, Italy
Interests: algorithms and complexity; algorithmic game theory; multi-agent systems; economic and computation
Prof. Dr. Luca Moscardelli
Guest Editor
Department of Economic Studies, University of Chieti-Pescara, Viale Pindaro 42, 65127 Pescara, Italy
Interests: algorithmic game theory; combinatorial optimization; communication networks; social networks

Special Issue Information

Dear Colleagues,

Multiagent systems have received tremendous attention in different disciplines, including computer science, artificial intelligence, civil engineering, medicine, etc. These systems are composed of self-governing and intelligent parts, called agents, which are autonomous, socially intelligent, reactive, and/or pro-active. They interact with each other, situated in a common environment, eventually participating to or building an organization. Each agent decides on a proper action to solve the task using multiple inputs, e.g., history of actions, interactions with other agents, or its own goal.

This Special Issue solicits papers addressing original research on foundations, theory, development, analysis, and applications of multiagent systems composed by autonomous agents. Topics of interest include economic paradigms (cooperative and non-cooperative algorithmic game theory); social choice and voting; mechanism design; cooperation and teamwork; distributed problem solving; coalition formation; agent societies and societal issues; social networks; trust and reputation; ethical and legal issues; privacy, safety and security; and learning (evolutionary algorithms, multiagent learning, reinforcement learning, deep learning).

Dr. Angelo Fanelli
Dr. Gianpiero Monaco
Prof. Dr. Luca Moscardelli
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 papers will be 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. Algorithms 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 1000 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.


  • Economic paradigms
  • Algorithmic game theory (cooperative and non-cooperative)
  • Social choice and voting
  • Mechanism design
  • Cooperation and teamwork
  • Coalition formation
  • Social networks
  • Privacy, safety, and security
  • Trust and reputation
  • Distributed problem solving
  • Learning
  • Evolutionary algorithms
  • Multiagent learning
  • Reinforcement learning
  • Deep learning

Published Papers

This special issue is now open for submission.
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