Tumer, Kagan; Agogino, Adrian Multiagent learning for black box system reward functions. (English) Zbl 1343.68208 Adv. Complex Syst. 12, No. 4-5, 475-492 (2009). Cited in 3 Documents MSC: 68T05 Learning and adaptive systems in artificial intelligence 68T42 Agent technology and artificial intelligence 91A26 Rationality and learning in game theory Keywords:multiagent learning; black box reward functions; multiagent coordination PDF BibTeX XML Cite \textit{K. Tumer} and \textit{A. Agogino}, Adv. Complex Syst. 12, No. 4--5, 475--492 (2009; Zbl 1343.68208) Full Text: DOI References: [1] DOI: 10.1007/s10458-006-6105-y · Zbl 05387288 · doi:10.1007/s10458-006-6105-y [2] DOI: 10.1162/evco.2008.16.2.257 · Zbl 05514038 · doi:10.1162/evco.2008.16.2.257 [3] Bagnell J. A., News Physiol. Sci. 18 [4] DOI: 10.2514/1.15242 · doi:10.2514/1.15242 [5] Bilimoria K. D., Air Traffic Cont. Q. 9 [6] DOI: 10.1016/S0378-4371(98)00260-X · doi:10.1016/S0378-4371(98)00260-X [7] R. H. Crites and A. G. Barto, Advances in Neural Information Processing Systems 8, eds. D. S. Touretzky, M. C. Mozer and M. E. Hasselmo (MIT Press, 1996) pp. 1017–1023. [8] Dietterich T. G., J. Artif. Intell. 13 pp 227– [9] Jefferies P., Phys. Rev. E 65 [10] Jennings N. R., Artif. Intell. 177 pp 277– [11] Kaelbling L. P., J. Artif. Intell. Res. 4 pp 237– [12] McGlohon M., Int. J. Lateral Comput. 1 pp 58– [13] DOI: 10.2514/2.4384 · doi:10.2514/2.4384 [14] Parkes D., News Physiol. Sci. 16 pp 791– [15] Stone P., Adapt. Behav. [16] DOI: 10.1109/9.664154 · Zbl 0904.90113 · doi:10.1109/9.664154 [17] DOI: 10.1007/978-1-4419-8909-3 · doi:10.1007/978-1-4419-8909-3 [18] Tuyls K., Artif. Intell. 171 [19] DOI: 10.1007/978-3-540-32274-0_18 · doi:10.1007/978-3-540-32274-0_18 [20] Whiteson S., Adapt. Behav. 15 [21] DOI: 10.1142/S0219525901000188 · Zbl 1058.91025 · doi:10.1142/S0219525901000188 This reference list is based on information provided by the publisher or from digital mathematics libraries. Its items are heuristically matched to zbMATH identifiers and may contain data conversion errors. It attempts to reflect the references listed in the original paper as accurately as possible without claiming the completeness or perfect precision of the matching.