creators_name: Metzger, Mary Ann type: journalp datestamp: 2001-03-31 lastmod: 2011-03-11 08:54:37 metadata_visibility: show title: A Step in the Right Direction ispublished: pub subjects: cog-psy subjects: comp-sci-neural-nets subjects: phil-dec-theory full_text_status: public keywords: Artificial neural networks, dynamical processes abstract: A review of W. Thomas Miller, III, Richard S. Sutton, and Paul J. Werbos (Eds.) Neural Networks for Control. Cambridge, Massachusetts: The MIT Press. 1990. pp. 524. This multi-disciplinary volume concerns the use of artificial neural networks in controlling dynamical processes. As used here 'dynamical' describes processes, such as certain chemical reaction systems, robots, or manufacturing plants, whose operation is governed by known or unknown non-linear models and which, therefore, are subject to certain types of problems related to unpredictability and chaotic performance. Artificial neural networks (ANN) are mathematical models whose components emulate the function of biological nervous systems. date: 1993-09 date_type: published publication: Journal of Mathematical Psychology volume: 37 number: 3 publisher: Academic Press pagerange: 477-485 refereed: TRUE referencetext: Anderson, D. B. O., Moore, J. B. and Hawkes, R. M. (1978) Model approximations via prediction error identification. Automatics. 14, 615-622. Carpenter, G. A., Grossberg, S., and Reynolds, J. H. (1991) ARTMAP: Supervised real-time learning and classification of nonstationary data by a self-organizing system. Neural Networks, 4, 565-588. Pole, A., West, M., and Harrison, J. (1988) Nonnormal and nonlinear dynamic Bayesian modeling. In J. C. Spall (ed.) Bayesian analysis of time series and dynamic models. New York: Marcell Dekker, Inc. West, M. and Harrison, J. (1989) Bayesian forecasting and dynamic models. Springer-Verlag New York Inc. citation: Metzger, Mary Ann (1993) A Step in the Right Direction. [Journal (Paginated)] document_url: http://cogprints.org/1424/1/cogprints/index.htm