Multi-Agent Systems: Planning, Perception and Control
A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Systems & Control Engineering".
Deadline for manuscript submissions: closed (15 May 2024) | Viewed by 2118
Special Issue Editor
Interests: fractional-order systems; dynamics; control; robotics; nonlocal operators; time-delay systems; optimization
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Multi-agent systems (MASs) have become increasingly important in various scientific and engineering fields, such as robotics, autonomous vehicles, swarm robotics, and traffic modeling. In these systems, planning helps agents to make informed decisions, perception enables them to understand their surroundings, and control ensures they execute the actions effectively. The growing interest in MAS is driven by the rising complexity of real-world challenges that require intelligent coordination among multiple agents. Integrating planning, perception, and control is at the core of advancing MAS, making research in this area both timely and crucial.
This Special Issue, ‘Multi-Agent Systems: Planning, Perception, and Control,’ aims to offer a platform for researchers and practitioners to share their insights on the latest developments, methodologies, and applications in the field of MAS. This very objective aligns seamlessly with one of the broader foci of MDPI, which is to advance knowledge and innovation in electronics, computer science, and engineering. MDPI has a longstanding tradition of publishing groundbreaking research, and we are confident that this Special Issue will continue this tradition.
We cordially invite submissions of original research articles and reviews that cover a wide range of topics related to the planning, perception, and control of multi-agent systems. While the list is not exhaustive, some suggested themes for submissions include the following:
- Multi-agent path planning and coordination;
- Perception and sensing in multi-agent systems;
- Strategies for controlling autonomous agents;
- Distributed control frameworks and paradigms;
- Applications of multi-agent systems in robotics, autonomous vehicles, and smart cities;
- Machine learning and artificial intelligence in multi-agent systems;
- Ethical and societal considerations in MAS.
Dr. Arman Dabiri
Guest Editor
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. Electronics 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
- multi-agent systems
- autonomous vehicles
- optimization
- sensing and fusion
- path and trajectory planning algorithms
- perception algorithms and technologies
- control strategies
- robotics
- swarm intelligence
- machine learning
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