Forming coalitions in the face of uncertain rewards
AAAI '94 Proceedings of the twelfth national conference on Artificial intelligence (vol. 1)
Learning to coordinate without sharing information
AAAI '94 Proceedings of the twelfth national conference on Artificial intelligence (vol. 1)
Communication in reactive multiagent robotic systems
Autonomous Robots
Collaborative plans for complex group action
Artificial Intelligence
Negotiation and cooperation in multi-agent environments
Artificial Intelligence - Special issue on economic principles of multi-agent systems
Coalitions among computationally bounded agents
Artificial Intelligence - Special issue on economic principles of multi-agent systems
Using collective intelligence to route Internet traffic
Proceedings of the 1998 conference on Advances in neural information processing systems II
Communication decisions in multi-agent cooperation: model and experiments
Proceedings of the fifth international conference on Autonomous agents
Learning sequences of actions in collectives of autonomous agents
Proceedings of the first international joint conference on Autonomous agents and multiagent systems: part 1
Designing agent collectives for systems with markovian dynamics
Proceedings of the first international joint conference on Autonomous agents and multiagent systems: part 3
Channeled multicast for group communications
Proceedings of the first international joint conference on Autonomous agents and multiagent systems: part 3
A Probabilistic Approach to Collaborative Multi-Robot Localization
Autonomous Robots
Asynchronous Teams: Cooperation Schemes for Autonomous Agents
Journal of Heuristics
Auctions with Severely Bounded Communication
FOCS '02 Proceedings of the 43rd Symposium on Foundations of Computer Science
Multiagent Reinforcement Learning: Theoretical Framework and an Algorithm
ICML '98 Proceedings of the Fifteenth International Conference on Machine Learning
Planning, Learning and Coordination in Multiagent Decision Processes
Proceedings of the Sixth Conference on Theoretical Aspects of Rationality and Knowledge
Toward Team-Oriented Programming
ATAL '99 6th International Workshop on Intelligent Agents VI, Agent Theories, Architectures, and Languages (ATAL),
Congregation Formation in Multiagent Systems
Autonomous Agents and Multi-Agent Systems
Collectives and Design Complex Systems
Collectives and Design Complex Systems
Coordinating multi-rover systems: evaluation functions for dynamic and noisy environments
GECCO '05 Proceedings of the 7th annual conference on Genetic and evolutionary computation
Multi-agent reward analysis for learning in noisy domains
Proceedings of the fourth international joint conference on Autonomous agents and multiagent systems
The communicative multiagent team decision problem: analyzing teamwork theories and models
Journal of Artificial Intelligence Research
Distributed agent-based air traffic flow management
Proceedings of the 6th international joint conference on Autonomous agents and multiagent systems
Theoretical Advantages of Lenient Learners: An Evolutionary Game Theoretic Perspective
The Journal of Machine Learning Research
A multiagent approach to managing air traffic flow
Autonomous Agents and Multi-Agent Systems
Coordinating learning agents for multiple resource job scheduling
ALA'09 Proceedings of the Second international conference on Adaptive and Learning Agents
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There are many domains in which a multi-agent system needs to maximize a "system utility" function which rates the performance of the entire system, while subject to communication restrictions among the agents. Such communication restrictions make it difficult for agents that take actions to optimize their own "private" utilities to also help optimize the system utility. In this article we show how previously introduced utilities that promote coordination among agents can be modified to be effective in domains with communication restrictions. The modified utilities provide performance improvements of up to 75 over previously used utilities in congestion games (i.e., games where the system utility depends solely on the number of agents choosing a particular action). In addition, we show that in the presence of severe communication restrictions, team formation for the purpose of information sharing among agents leads to an additional 25 improvement in system utility. Finally, we show that agents' private utilities and team sizes can be manipulated to form the best compromise between how "aligned" an agent's utility is with the system utility and how easily an agent can learn that utility.