Summary
Individuals in large, heterogeneous teams will commonly produce sensor data that is likely useful to some other members of the team, but it is not precisely known to whom the information is useful. Some recent work has shown that randomly propagating the information performed surprisingly well, compared to infeasible optimal approaches. This chapter extends that work by looking at how the relative performance of random information passing algorithms scales with the size of the team. Additionally, the chapter looks at how random information passing performs when sensor data is noisy, so that individuals need multiple pieces of data to reach a conclusion, and the underlying situation is dynamic, so individuals need new information over time. Results show that random information passing is broadly effective, although relative performance is lower in some situations.
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References
Bourgault, F., Durrant-Whyte, H.: Communication in general decentralized filter and the coordinated search strategy. In: Proc. of FUSION’04 (2004)
Boyd, S., Ghosh, A., Prabhakar, B., Shah, D.: Randomized gossip algorithms. IEEE/ACM Trans. Netw. 14(SI), 2508–2530 (2006). doi:10.1109/TIT.2006.874516
Chaimowicz, L., Kumar, V.: Aerial shepherds: Coordination among uavs and swarms of robots. In: 7th International Symposium on Distributed Autonomous Robotic Systems (2004)
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)
Goldman, C.V., Zilberstein, S.: Optimizing information exchange in cooperative multi-agent systems. In: Proceedings of the Second International Conference on Autonomous Agents and Multi-agent Systems (2003)
Heinzelman, W.R., Kulik, J., Balakrishnan, H.: Adaptive protocols for information dissemination in wireless sensor networks. In: Proc. of MobiCom’99 (1999)
Kuokka, D., Harada, L.: Matchmaking for information agents. In: Readings in Agents. Morgan Kaufmann, San Mateo (1995)
Kuokka, D., Harada, L.: Matchmaking for information agents. In: Readings in Agents. Morgan Kaufmann, San Mateo (1997)
Leary, C.C., Schwehm, M., Eichner, M., Duerr, H.P.: Tuning degree distributions: Departing from scale-free networks. Phys. A, Stat. Mech. Appl. 382(2), 731–738 (2007)
Nair, R., Tambe, M.: Communication for improving policy computation in distributed pomdps. In: Proc. of AAMAS’04 (2004)
Rosencrantz, M., Gordon, G., Thrun, S.: Decentralized sensor fusion with distributed particle filters. In: Proceedings of the Conference on Uncertainty in AI (UAI) (2003)
Roth, M.: Execution-time communication decisions for coordination of multi-agent teams. PhD thesis, Robotics Institute, Carnegie Mellon Univ., Pittsburgh, PA (2007)
Schurr, N., Marecki, J., Tambe, M., Scerri, P., Levis, J., Kasinadhuni, N.: The future of disaster response: Humans working with multiagent teams using DEFACTO. In: AAAI Spring Symposium on Homeland Security (2005)
Tambe, M.: Agent architectures for flexible, practical teamwork. In: National Conference on AI (AAAI97), pp. 22–28 (1997)
Velagapudi, P., Prokopyev, O., Sycara, K., Scerri, P.: Maintaining shared belief in a large multiagent team. In: Proceedings of FUSION’07 (2007)
Velagapudi, P., Prokopyev, O., Sycara, K., Scerri, P.: An analysis of information sharing in large teams. In: Proceedings of AAMAS’09 (2009)
Xu, Y., Scerri, P., Yu, B., Okamoto, S., Lewis, M., Sycara, K.: An integrated token-based algorithm for scalable coordination. In: AAMAS’05 (2005)
Xuan, P., Lesser, V., Zilberstein, S.: Communication decisions in multi-agent cooperation: Model and experiments. In: Proceedings of the Fifth International Conference on Autonomous Agents (2001)
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Scerri, P., Velagapudi, P., Sycara, K. (2010). Analyzing the Theoretical Performance of Information Sharing. In: Hirsch, M., Pardalos, P., Murphey, R. (eds) Dynamics of Information Systems. Springer Optimization and Its Applications, vol 40. Springer, New York, NY. https://doi.org/10.1007/978-1-4419-5689-7_7
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DOI: https://doi.org/10.1007/978-1-4419-5689-7_7
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