TY - GEN
T1 - Distributed Constraint Optimization for large teams of mobile sensing agents
AU - Zivan, Roie
AU - Glinton, Robin
AU - Sycara, Katia
PY - 2009/12/1
Y1 - 2009/12/1
N2 - A team of mobile sensors can be used for coverage of targets in different environments. The dynamic nature of such an application requires the team of agents to adjust their locations with respect to changes which occur. The dynamic nature is caused by environment changes, changes in the agents' tasks and by technology failures. A new model for representing problems of mobile sensor teams based on Distributed Constraint Optimization Problems (DCOP), is proposed. The proposed model, needs to handle a dynamic problem in which the alternative assignments for agents and set of neighbors, derive from their physical location which is dynamic. DCOP-MST enables representation of variant dynamic elements which a team of mobile sensing agents face. A reputation model is used to determine the credibility of agents. By representing the dynamic sensing coverage requirements in the same scale as the agents' credibility, the deployment of sensors in the area can be evaluated and adjusted with correspondence to dynamic changes. In order to solve a DCOP-MST, a local (incomplete) search algorithm (MGM-MST) based on the MGM algorithm is proposed and combined with various exploration methods. While existing exploration methods are evidently not effective in DCOP-MSTs, new exploration methods which are designed for these special applications are found to be successful in our experimental study.
AB - A team of mobile sensors can be used for coverage of targets in different environments. The dynamic nature of such an application requires the team of agents to adjust their locations with respect to changes which occur. The dynamic nature is caused by environment changes, changes in the agents' tasks and by technology failures. A new model for representing problems of mobile sensor teams based on Distributed Constraint Optimization Problems (DCOP), is proposed. The proposed model, needs to handle a dynamic problem in which the alternative assignments for agents and set of neighbors, derive from their physical location which is dynamic. DCOP-MST enables representation of variant dynamic elements which a team of mobile sensing agents face. A reputation model is used to determine the credibility of agents. By representing the dynamic sensing coverage requirements in the same scale as the agents' credibility, the deployment of sensors in the area can be evaluated and adjusted with correspondence to dynamic changes. In order to solve a DCOP-MST, a local (incomplete) search algorithm (MGM-MST) based on the MGM algorithm is proposed and combined with various exploration methods. While existing exploration methods are evidently not effective in DCOP-MSTs, new exploration methods which are designed for these special applications are found to be successful in our experimental study.
UR - http://www.scopus.com/inward/record.url?scp=77957873128&partnerID=8YFLogxK
U2 - 10.1109/WI-IAT.2009.176
DO - 10.1109/WI-IAT.2009.176
M3 - Conference contribution
AN - SCOPUS:77957873128
SN - 9780769538013
T3 - Proceedings - 2009 IEEE/WIC/ACM International Conference on Intelligent Agent Technology, IAT 2009
SP - 347
EP - 354
BT - Proceedings - 2009 IEEE/WIC/ACM International Conference on Intelligent Agent Technology, IAT 2009
T2 - 2009 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology, WI-IAT 2009
Y2 - 15 September 2009 through 18 September 2009
ER -