The Living Thing / Notebooks :

Distributed sensing and swarm sensing

Is this is a real field separate from all the things that looks similar to it? e.g.probability collectives (are they a thing?) and the nature-inspired algorithms people get disturbingly enthusiastic about (ant colonies, particle swarms, that one based on choirs…), and reliability engineering (Byzantine generals etc), …and quorum sensing? How about that?

Although this looks a little bit like collective decisions, this should be a design-oriented. When we say “multi agent systems” there is usually a presumption that the individual agents are fairly simple, not whole human beings. Simpler still, distributed statistics is about algorithms that approximate or approach statistics in a distributed fashion. Special case, flocking. The barriers betwixt these are permeable.

Links to those themes:

Refs

ASSC02
Akyildiz, I. F., Su, W., Sankarasubramaniam, Y., & Cayirci, E. (2002) A survey on sensor networks. Communications Magazine, IEEE, 40(8), 102–114.
BiWo04
Bieniawski, S., & Wolpert, D. H.(2004) Adaptive, distributed control of constrained multi-agent systems. In Proceedings of the Third International Joint Conference on Autonomous Agents and Multiagent Systems-Volume 3 (Vol. 4, pp. 1230–1231). IEEE Computer Society
CoVa04
Codenotti, B., & Varadarajan, K. (2004) Efficient computation of equilibrium prices for markets with Leontief utilities. In ICALP (pp. 371–382). Springer DOI.
Degr74
Degroot, M. H.(1974) Reaching a Consensus. Journal of the American Statistical Association, 69(345), 118–121. DOI.
DePS02
Deng, X., Papadimitriou, C., & Safra, S. (2002) On the Complexity of Equilibria. In Proceedings of the Thiry-fourth Annual ACM Symposium on Theory of Computing (pp. 67–71). New York, NY, USA: ACM DOI.
LaJS14
Lalitha, A., Javidi, T., & Sarwate, A. (2014) Social Learning and Distributed Hypothesis Testing. ArXiv:1410.4307 [Cs, Math, Stat].
Olfa05
Olfati-Saber, R. (2005) Distributed Kalman Filter with Embedded Consensus Filters. In 44th IEEE Conference on Decision and Control, 2005 and 2005 European Control Conference. CDC-ECC ’05 (pp. 8179–8184). DOI.
Olfa06
Olfati-Saber, R. (2006) Flocking for multi-agent dynamic systems: Algorithms and theory. Automatic Control, IEEE Transactions On, 51(3), 401–420.
OlFM07
Olfati-Saber, R., Fax, J. A., & Murray, R. M.(2007) Consensus and Cooperation in Networked Multi-Agent Systems. Proceedings of the IEEE, 95(1), 215–233. DOI.
RLPB06
Rajasegarar, S., Leckie, C., Palaniswami, M., & Bezdek, J. C.(2006) Distributed Anomaly Detection in Wireless Sensor Networks. In 10th IEEE Singapore International Conference on Communication systems, 2006. ICCS 2006 (pp. 1–5). DOI.
ReBe05
Ren, W., & Beard, R. W.(2005) Consensus seeking in multiagent systems under dynamically changing interaction topologies. Automatic Control, IEEE Transactions On, 50(5), 655–661.
SoBe17
Softky, W., & Benford, C. (2017) Sensory Metrics of Neuromechanical Trust. Neural Computation, 29(9), 2293–2351. DOI.
TuWo04
Tumer, K., & Wolpert, D. H.(2004) Coordination in Large Collectives- Chapter 1.
Wolp06
Wolpert, D. H.(2006) Advances in Distributed Optimization Using Probability Collectives. Advances in Complex Systems, 9.
WoBR11
Wolpert, D. H., Bieniawski, S. R., & Rajnarayan, D. G.(2011) Probability Collectives in Optimization.
WoLa02
Wolpert, D. H., & Lawson, J. W.(2002) Designing agent collectives for systems with Markovian dynamics. (pp. 1066–1073). Presented at the Proceedings of the first international joint conference on Autonomous agents and multiagent systems: part 3 DOI.
WoTu99
Wolpert, D. H., & Tumer, K. (1999) An Introduction to Collective Intelligence. ArXiv:Cs/9908014.
WoWT99
Wolpert, D. H., Wheeler, K. R., & Tumer, K. (1999) General principles of learning-based multi-agent systems. (pp. 77–83). Presented at the Proceedings of the third annual conference on Autonomous Agents DOI.
WoWT00
Wolpert, D. H., Wheeler, K. R., & Tumer, K. (2000) Collective intelligence for control of distributed dynamical systems. EPL (Europhysics Letters), 49, 708. DOI.
Ye08
Ye, Y. (2008) A path to the Arrow–Debreu competitive market equilibrium. Mathematical Programming, 111(1–2), 315–348. DOI.