Large-scale information retrieval with latent semantic indexing
Information Sciences: an International Journal
Coalitions among computationally bounded agents
Artificial Intelligence - Special issue on economic principles of multi-agent systems
Methods for task allocation via agent coalition formation
Artificial Intelligence
Coalition structure generation with worst case guarantees
Artificial Intelligence
Coalition formation with uncertain heterogeneous information
AAMAS '03 Proceedings of the second international joint conference on Autonomous agents and multiagent systems
The Advantages of Compromising in Coalition Formation with Incomplete Information
AAMAS '04 Proceedings of the Third International Joint Conference on Autonomous Agents and Multiagent Systems - Volume 2
Web personalisation for users protection: a multi-agent method
ITWP'03 Proceedings of the 2003 international conference on Intelligent Techniques for Web Personalization
Autonomic communication services: a new challenge for software agents
Autonomous Agents and Multi-Agent Systems
Searching for agent coalition using particle swarm optimization and death penalty function
ICIC'07 Proceedings of the intelligent computing 3rd international conference on Advanced intelligent computing theories and applications
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Recent studies have shown that compromise may facilitate coalition formation and increase agent utilities. In this study we leverage on those results. We devise a novel coalition formation mechanism that enhances compromise. Our mechanism can utilize information on task relationships to reduce formation complexity. The suggested mechanism works well with both cardinal and ordinal task values. Via experiments we show that the use of the suggested compromise-based coalition formation mechanism provides significant savings in the computation and communication complexity of coalition formation. Our results also show that when information on task relationships is used, the complexity of coalition formation is further reduced. We demonstrate successful use of the mechanism for collaborative information filtering, where agents combine linguistic rules to analyze documents' contents.