Learning Situation-Specific Coordination in Cooperative Multi-agent Systems
Autonomous Agents and Multi-Agent Systems
Vague Regions and Spatial Relationships: A Rough Set Approach
ICCIMA '01 Proceedings of the Fourth International Conference on Computational Intelligence and Multimedia Applications
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The evaluation and management of sensor uncertainty is particularly necessary in a noisy multi-sensor context. In this paper, focusing on the potential of distributed coordination among sensor nodes based on the built-in association between wireless sensor networks and multi-agent systems, meanwhile in a rough set technique senseof uncertainty, we show how an adaptive distributed coordination framework for a hierarchy of sensor data uncertainty performs local data fusion to increase the certainty of real-time sensor readings coherently, makes global rational decisions under imprecision and partial truth, and reconciles the conflicts somewhat, thus evolving adaptive and robust sensor uncertainty handling systems. Implementation results for an example sensor field demonstrate the application of our proposed approach.