Artificial Intelligence and Multi-Agent Systems for Big Data
A special issue of Big Data and Cognitive Computing (ISSN 2504-2289).
Deadline for manuscript submissions: closed (31 December 2022) | Viewed by 805
Special Issue Editors
Interests: multiagent systems; autonomous navigation; SLAM
Special Issues, Collections and Topics in MDPI journals
Interests: networked control systems; robust control; reinforcement learning
Interests: SLAM; autonomous navigation; multi-robot systems; deep learning for anomaly detection; FPGA-based algorithm acceleration
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
With the development of single-agent technology in various fields such as defense, logistics, surveillance, and social services, the interest and research on multi-agent systems (MASs or "self-organized system") are being concentrated in recent years. An MAS is a computerized system composed of multiple interacting intelligent agents. MASs can solve problems that are difficult or impossible for a single agent or a monolithic system to solve.
The evolution of research in Artificial Intelligence (AI) and Big Data in recent years challenges almost all domains of human activity. The potential of AI to act as a catalyst for all given business models, and the capacity of Big Data research to provide sophisticated data and services ecosystems at a global scale, provide a challenging context for scientific contributions and applied research.
In this Special Issue, we would like to include outstanding studies for aforementioned topics such as original research articles or comprehensive review papers. The scope of “Artificial Intelligence and Big Data for Multi-Agent Systems” includes, but is not limited to, the following topics:
- Challenges and Problems in Multi-agent Systems;
- Cooperative Control based on Deep Learning;
- Modeling and Simulation for Multi-agent Systems;
- Intelligent and Collective mapping;
- Swarm Intelligence;
- Swarms of Drones;
- Swarms and Swarm Intelligence;
- Sensor Networks;
- Biomimetics and Bio-inspired Robotics;
- Decentralized Control and Distributed Systems;
- Deep Learning for Swarm Robotics;
- Self-organization and Self-assembly;
- Collective Movement and Task Allocation;
- Intelligent Scheduling for Multi-agent systems;
- Control Algorithm for Drone Swarms;
- Collective Transport of Objects;
- Collective Mapping
- Swarm Robotics and Behavior Models;
- Local and Global Sensing and Communications;
- Safety Analysis of Swarm Robotics;
- Development of AI Methodologies and Practices;
- Intelligent Robot Algorithms Development;
- Cooperative Robotics in IoT Ecosystems;
- The Internet of Robotic Things.
Prof. Dr. Seunghwan Lee
Prof. Dr. Jaepil Ban
Prof. Dr. Heoncheol Lee
Guest Editors
Manuscript Submission Information
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Keywords
- multi-agent systems
- artificial intelligence
- big data
- cooperative control
- collective mapping
- swarm robotics
- cooperative robotics
- sensor network
- deep learning
- collective intelligence
- communication
- drone swarms
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