Coalition formation with uncertain heterogeneous information
AAMAS '03 Proceedings of the second international joint conference on Autonomous agents and multiagent systems
Coalition formation through motivation and trust
AAMAS '03 Proceedings of the second international joint conference on Autonomous agents and multiagent systems
Self-organization through bottom-up coalition formation
AAMAS '03 Proceedings of the second international joint conference on Autonomous agents and multiagent systems
Agent-organized networks for dynamic team formation
Proceedings of the fourth international joint conference on Autonomous agents and multiagent systems
A utility-based sensing and communication model for a glacial sensor network
AAMAS '06 Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems
Coalition Formation: From Software Agents to Robots
Journal of Intelligent and Robotic Systems
The Contract Net Protocol: High-Level Communication and Control in a Distributed Problem Solver
IEEE Transactions on Computers
Methods for Coalition Formation in Adaptation-Based Social Networks
CIA '07 Proceedings of the 11th international workshop on Cooperative Information Agents XI
Social knowledge and social action: heterogeneity in practice
IJCAI'93 Proceedings of the 13th international joint conference on Artifical intelligence - Volume 1
IEEE Communications Magazine
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Wireless Sensor Networks are generally composed of a large number of nodes that monitor their surrounding area. The monitoring capacity of sensors gets altered by the changing conditions of the environment and the sensors' internal state. Sensor coalitions, in which only the leader transmits information to a sink node, are a means to save resources when the conditions of the environment are similar around the sensors in the coalition. In this paper we analyse and formalise such sensor coalitions and propose an algorithm for coalition formation that allows the sensors to self-organise with the purpose of performing a good monitoring of the environment while maximising the life span of the sensor network as a whole. The algorithm uses the quality of the information fused at the coalition leader and the remaining energy of the sensors as the basic parameters to alter coalition membership and leadership.