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Home NEWS Science News

New study describes multi-agent systems for optimization and decision-making through games

Bioengineer by Bioengineer
May 10, 2022
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In artificial intelligence, multi-agent systems can be thought of as a society of individuals (agents) that interact by exchanging knowledge and by negotiating with each other to achieve an individual/global goal. In real life, multi-agent systems are used in many diverse fields like resource management; information security; manufacturing planning, scheduling, and control; monitoring, diagnosis, and control; e-commerce; biomedicine; and virtual enterprise. Given their immense usefulness, researchers are constantly trying to find new ways to use these systems in real-world settings.

Multi-Agent Systems: An Optimization and Game Theory Perspective

Credit: Chinese Association of Automation

In artificial intelligence, multi-agent systems can be thought of as a society of individuals (agents) that interact by exchanging knowledge and by negotiating with each other to achieve an individual/global goal. In real life, multi-agent systems are used in many diverse fields like resource management; information security; manufacturing planning, scheduling, and control; monitoring, diagnosis, and control; e-commerce; biomedicine; and virtual enterprise. Given their immense usefulness, researchers are constantly trying to find new ways to use these systems in real-world settings.

Against this background, a group of researchers led by Prof. Yang Tang, from East China University of Science and Technology, Shanghai, China, together with Prof. Qing-Long Han, a member of the Academia Europaea and IEEE Fellow from Swinburne University of Technology, Melbourne, Australia, and Prof.  Jürgen Kurths, a member of the Academia Europaea from Potsdam Institute for Climate Impact Research, Potsdam, Germany, work together to dig deep into issues related to multi-agent systems. They probe into the nature of cooperative/non-cooperative behaviors of multi-agent systems from optimization to games, as an approach to solving complex real-world problems. They published their findings in the May Issue, IEEE/CAA Journal of Automatica Sinica, a joint publication by The Institute of Electrical and Electronics Engineers (IEEE) and Chinese Association of Automation (CAA).

“Multi-agent systems often involve multi-objective optimization with conflicting objectives, and each object is inevitably affected by uncertainty. Therefore, game theory can endow multi-agent systems with more solutions and provide a means of interdisciplinary integration, such as the integration of games and control, AI, mathematics, and other disciplines,” claims Prof. Tang and Prof. Kurths.

They considered game theory for a very important reason. To put it simply, games, especially turn-based strategy games, are everywhere around us. Games are specific to situations with interdependence and can be divided into cooperative games and non-cooperative games, or classified into static games and dynamic games, according to the behaviors and action sequence of agents. The researchers have integrated the two classifications for a more comprehensive view of complex real-world scenarios.

In their survey, the authors used game theory to create models of cooperative or competitive behaviors for individual or global optimization goals. The focus was on three aspects of cooperation and competition in multi-agent systems: cooperative optimization, cooperative games, and non-cooperative games. “For game-related problems, a non-cooperative game is formed when an agent’s goal may be different or completely opposite to that of other agents; conversely, a cooperative game is formed when an agent absolutely cooperate with other agents and consider common interests,” clarifies Mr. Wang and Mr. Hong.

The survey tackles multiple angles: first, it focuses on distributed online optimization, federated optimization, and their applications in privacy protection. Then, by focusing on static and dynamic games with cooperative and competitive factors, respectively, the study bridges the transition from cooperative optimization to cooperative games in a novel way.

So where can these findings be used? The applications are multifold, according to the authors.

Using a particularly illustrative example, Prof. Han says, “In smart cities, these findings can be used to build an intelligent traffic decision-making system relying on urban big data. This means that the duration of traffic lights at intersections can be optimized, so that the traffic flow can be adjusted, the load of the road network can be balanced, and the utilization efficiency of road resources can be improved.”

The applications also range across other fields. In economics, market competition can be modeled as a game problem. In the field of information security, non-cooperative attack-defense games can be constructed to find the optimal defense strategy by identifying the intention of the interaction information and predicting the aggressive behavior. Even in drug development, cooperative games can be constructed to obtain the maximum utility of the macromolecular structure.

Clearly, game theory is a game-changer for multi-agent systems!

J. R. Wang, Y. T. Hong, J. L. Wang, J. P. Xu, Y. Tang, Q.-L. Han, and J. Kurths, “Cooperative and competitive multi-agent systems: From optimization to games,” IEEE/CAA J. Autom. Sinica, vol. 9, no. 5, pp. 763–783, May 2022. DOI: 10.1109/JAS.2022.105506

###

IEEE/CAA Journal of Automatica Sinica aims to publish high-quality, high-interest, far-reaching research achievements globally, and provide an international forum for the presentation of original ideas and recent results related to all aspects of automation.

The Impact Factor of IEEE/CAA Journal of Automatica Sinica is 6.171, ranking among Top 11% (7/63, SCI Q1) in the category of Automation & Control Systems, according to the latest Journal Citation Reports released by Clarivate Analytics in 2021. In addition, its latest CiteScore is 11.2, and has entered Q1 in all three categories it belongs to (Information System, Control and Systems Engineering, Artificial Intelligence) since 2018. 

Why publish with us: Fast and high quality peer review; Simple and effective online submission system; Widest possible global dissemination of your research; Indexed in SCIE, EI, IEEE, Scopus, Inspec. JAS papers can be found at http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=6570654 or www.ieee-jas.net



Journal

IEEE/CAA Journal of Automatica Sinica

DOI

10.1109/JAS.2022.105506

Article Title

Cooperative and Competitive Multi-Agent Systems: From Optimization to Games

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