Multi-agent systems
From International Center for Computational Logic
Multi-agent systems
Multi-agent systems (MAS) focus on the interaction of autonomous agents—entities capable of independent decision-making—situated in a shared environment. MAS research investigates how agents can cooperate, compete, or coordinate their actions to achieve individual or collective goals. The theoretical foundations of this field draw from game theory, social choice, distributed computing, and artificial intelligence more broadly. A key concern in MAS is the design of mechanisms that enable efficient collaboration or competition among agents, particularly when they act based on clear objectives. In our research, we often assume that agents are presented with a set of possible choices. While all the agents are aware of these choices, they do not know which option represents the correct or superior choice—the ground truth. In such systems, the agents collaborate with the objective of identifying this ground truth, which remains unknown to them at the outset.
Professors and Research Group Leaders
Scientific Staff
Proceedings Articles
Lea Bauer, Jonas Karge
Multi-Agent Opinion Pooling by Voting for Bins: Simulations and Characterization
22nd International Conference on Practical Applications of Agents and Multi-Agent Systems (PAAMS2024), 2024
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Jonas Karge, Juliette-Michelle Burkhardt, Sebastian Rudolph, Dominik Rusovac
To Lead or to be Led: A Generalized Condorcet Jury Theorem under Dependence
AAMAS '24: Proceedings of the 2024 International Conference on Autonomous Agents and Multiagent Systems, 2024
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Jonas Karge
Taming Dilation in Imprecise Pooling
Proceedings of the International Conference on Principles and Practice of Multi-Agent Systems (PRIMA), 2024
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Jonas Karge
Voting for Bins: Integrating Imprecise Probabilistic Beliefs into the Condorcet Jury Theorem
Proceedings of the The 2nd International Workshop on Knowledge Diversity (KoDis23), 2023
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