Abstract
The performance of a cooperative team depends on the views that individual team members build of the environment in which they are operating. Teams with many vehicles and sensors generate a large amount of information from which to create those views. However, bandwidth limitations typically prevent exhaustive sharing of this information. As team size and information diversity grows, it becomes even harder to provide agents with needed information within bandwidth constraints, and it is impractical for members to maintain any detailed information for every team mate. Building on previous token-based algorithms, this chapter presents an approach for efficiently sharing information in large teams. The key distinction from previous work is that this approach models differences in how agents in the team value knowledge and certainty about features. By allowing the tokens passed through the network to passively estimate the value of certain types of information to regions of the network, it is possible to improve token routing through the use of local decision-theoretic models. We show that intelligent routing and stopping can increase the amount of locally useful information received by team members while making more efficient use of agents’ communication resources.
This research has been sponsored in part by AFOSR FA9550-07-1-0039 and AFOSR FA9620-01-1-0542.
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References
Uryasev, S.: Conditional value-at-risk: Optimization algorithms and applications. Financial Engineering News 14, 1–5 (2000)
Drury, J.L., Richer, J., Rackliffe, N., Goodrich, M.A.: Comparing situation awareness for two unmanned aerial vehicle human interface approaches. In: Proceedings of the IEEE International Workshop on Safety, Security and Rescue Robotics (2006)
Grocholsky, B.: Information-Theoretic Control of Multiple Sensor Platforms. PhD thesis, The University of Sydney (2002)
Makarenko, A., Brooks, A., Williams, S.B., Durrant-Whyte, H.F., Grocholsky, B.: An architecture for decentralized active sensor networks. In: IEEE International Conference on Robotics and Automation (ICRA 2004), New Orleans, LA, USA (2004)
Nettleton, E., Thrun, S., Durrant-Whyte, H.: Decentralized slam with low-bandwidth communication for teams of airborne vehicles. In: Proc. of International Conference on Field and Service Robotics (2003)
Ortiz, C.L., Vincent, R., Morisset, B.: Task inference and distributed task management in centibots robotic systems. In: AAMAS (2005)
Rosencrantz, M., Gordon, G., Thrun, S.: Decentralized sensor fusion with distributed particle filters. In: Proceedings of the Conference on Uncertainty in AI (UAI) (2003)
Tambe, M.: Agent architectures for flexible, practical teamwork. National Conference on AI (AAAI 1997), pp. 22–28 (1997)
Velagapudi, P., Prokopyev, O., Sycara, K., Scerri, P.: Maintaining shared belief in a large multiagent team. In: Proceedings of Tenth International Conference on Information Fusion (2007)
Watts, D., Strogatz, S.: Collective dynamics of small world networks. Nature 393, 440–442 (1998)
Xu, Y., Lewis, M., Sycara, K., Scerri, P.: Information sharing in very large teams. In: AAMAS 2004 Workshop on Challenges in Coordination of Large Scale MultiAgent Systems (2004)
Xu, Y., Scerri, P., Yu, B., Okamoto, S., Lewis, M., Sycara, K.: An integrated token-based algorithm for scalable coordination. In: AAMAS 2005 (2005)
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Velagapudi, P., Prokopyev, O., Scerri, P., Sycara, K. (2009). A Token-Based Approach to Sharing Beliefs in a Large Multiagent Team. In: Hirsch, M.J., Commander, C.W., Pardalos, P.M., Murphey, R. (eds) Optimization and Cooperative Control Strategies. Lecture Notes in Control and Information Sciences, vol 381. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-88063-9_24
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DOI: https://doi.org/10.1007/978-3-540-88063-9_24
Publisher Name: Springer, Berlin, Heidelberg
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