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All Outputs (6)

A communication architecture for multi-agent learning systems (2000)
Book Chapter
Ireson, N., Cao, Y., Bull, L., & Miles, R. (2000). A communication architecture for multi-agent learning systems. In S. Cagnoni, R. Poli, G. D. Smith, D. Corne, M. Oates, E. Hart, …T. C. Fogarty (Eds.), Real-World Applications of Evolutionary Computing: EvoWorkshops 2000 (119-147). Springer

Self-adaptive mutation in ZCS controllers (2000)
Journal Article
Bull, L., & Hurst, J. (2000). Self-adaptive mutation in ZCS controllers. Lecture Notes in Artificial Intelligence, 1803, 339-346. https://doi.org/10.1007/3-540-45561-2_33

© Springer-Verlag Berlin Heidelberg 2000. The use and benefits of self-adaptive mutation operators are well-known within evolutionary computing. In this paper we examine the use of self-adaptive mutation in Michigan-style Classifier Systems with the... Read More about Self-adaptive mutation in ZCS controllers.

Self-adaptive mutation in classifier system controllers (2000)
Book Chapter
Bull, L., Hurst, J., & Tomlinson, A. (2000). Self-adaptive mutation in classifier system controllers. In J. Meyer, A. Berthoz, D. Floreano, H. L. Roitblat, & S. W. Wilson (Eds.), From Animals to Animats 6 (460-467). MIT Press

Distributed learning control of traffic signals (2000)
Journal Article
Bull, L., Cao, Y. J., Ireson, N., Bull, L., & Miles, R. (2000). Distributed learning control of traffic signals. Lecture Notes in Artificial Intelligence, 1803, 117-126. https://doi.org/10.1007/3-540-45561-2_12

© Springer-Verlag Berlin Heidelberg 2000. This paper presents a distributed learning control strategy for traffic signals. The strategy uses a fully distributed architecture in which there is effectively only one (low) level of control. Such strategy... Read More about Distributed learning control of traffic signals.