Distributed constraint optimization for mobile sensor teams
AAMAS(2014)
摘要
Coordinating a team of mobile sensing agents (MST) to adequately position themselves with regards to points of interest generally called targets (e.g., disaster survivors, military targets, or pollution spills), is a challenging problem in many multiagent applications. Such applications are inherently dynamic due to changes in the environment, technology failures, and incomplete knowledge of the agents. Agents must adaptively respond by changing their locations to continually optimize the coverage of targets. Optimally choosing where to position the agents to meet the coverage requirements in a static setting is a known NP-hard optimization problem. Doing so in a dynamic distributed environment is a challanging task. In this work I develop and study the DCOP MST model which is a new model for representing MST problems that is based on the Distributed Constraint Optimization (DCOP) Framework.
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关键词
challanging task,mst problem,disaster survivor,np-hard optimization problem,new model,challenging problem,constraint optimization,mobile sensor team,optimally choosing,coverage requirement,dcop mst model
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