Forming coalitions in the face of uncertain rewards
AAAI '94 Proceedings of the twelfth national conference on Artificial intelligence (vol. 1)
Coalitions among computationally bounded agents
Artificial Intelligence - Special issue on economic principles of multi-agent systems
LICS '96 Proceedings of the 11th Annual IEEE Symposium on Logic in Computer Science
Coalition formation with uncertain heterogeneous information
AAMAS '03 Proceedings of the second international joint conference on Autonomous agents and multiagent systems
Searching for Optimal Coalition Structures
ICMAS '00 Proceedings of the Fourth International Conference on MultiAgent Systems (ICMAS-2000)
Towards Agent-Based Coalition Formation for Service Composition
IAT '06 Proceedings of the IEEE/WIC/ACM international conference on Intelligent Agent Technology
Dynamic Coalition of Resource-Bounded Autonomous Agents
ICTAI '07 Proceedings of the 19th IEEE International Conference on Tools with Artificial Intelligence - Volume 01
Task allocation via coalition formation among autonomous agents
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 1
Methods for task allocation via agent coalition formation
Artificial Intelligence
A kernel-oriented model for coalition-formation in general environments: implementation and results
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 1
Biologically inspired coalition formation of multi-agent systems
Proceedings of the 9th International Conference on Autonomous Agents and Multiagent Systems: volume 1 - Volume 1
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Male bottlenose dolphins, Tursiops truncatus, found off the coast of Western Australia and Florida, often form varied levels of alliances to capture females and increase their chances of mating. One such alliance, known as the first-order alliance, consists of 2-3 dolphins that share a very strong "bond", formally known as the Association coefficient in behavioral biology. We formalize factors that affect the coefficient, and analyze their influence in building alliances in the context of multi-agent coalition formation. We produce a model of the first-order alliance as a hybrid automation, based solely on local information evolving over spatially defined interaction topologies, where the model is expressive enough to capture the biological phenomenon, yet simple enough to derive results through analysis.