Zalecana literatura:
M. Bishop, Pattern Recognition and Machine Learning, Springer, 2006.
A. P. Engelbrecht, Computational Intelligence an Introduction, Wiley, 2003.
M. Bishop, Neural Networks for Pattern Recognition, Oxford University Press, 1995.
S. Haykin, An Introduction to Neural Networks, Prentice Hall; 2nd edition 1998.
L. Rutkowski, Metody i techniki sztucznej inteligencji, Wydawnictwo Naukowe PWN, 2005.
P. Cichosz, Systemy uczące się, WNT, Warszawa, 2007.
Brzózka Jerzy, Dorobczyński Lech, Matlab. Środowisko obliczeń naukowo-technicznych, MIKOM, 2005.
S. Osowski, Sieci neuronowe w ujęciu algorytmicznym, WNT 1996.
J. Zurada, M. Barski, W. Jędruch, Sztuczne sieci neuronowe, PWN 1996.
W. Duch, J. Korbicz, L. Rutkowski, R. Tadeusiewicz, "Biocybernetyka i Inzynieria Biomedyczna 2000", tom 6, "Sieci Neuronowe", AOW 2000.
J. Korbicz, A. Obuchowicz, D. Uciński, Sztuczne sieci neuronowe. Podstawy i zastosowania, Akademicka Oficyna Wydawnicza, 1994.
K. Gurney, An Introduction to Neural Networks CRC (August 5, 1997), ISBN-10: 1857285034
M.A. Arbib, 1989, The Metaphorical Brain 2: Neural Networks and Beyond,
Wiley-Interscience.
M.A. Arbib, Ed., 1995, The Handbook of Brain Theory
and Neural Networks, MIT Press (paperback).
Michael A. Arbib, and
Jeffrey Grethe, Editors, 2001, Computing the Brain: A Guide to Neuroinformatics,
and the Project Team of the University of Southern California Brain Project, San
Diego: Academic Press.
A. Weitzenfeld, M.A. Arbib and A. Alexander, 2000,
NSL Neural Simulation Language, MIT Press (in press).
[http://www-hbp.usc.edu/_Documentation/NSL/Book/TOC.htm]
J. J. Hopfield, "Neural networks and physical systems with emergent collective computational abilities", Proceedings of the National Academy of Sciences of the USA, vol. 79 no. 8 pp. 2554-2558, April 1982.
Baxter, J., Tridgell, A., Weaver, L. (1998). KnightCap: A
chess program that learns by combining TD() with game-tree search. Proceedings
of the Fifteenth International Conference on Machine Learning, pp. 28-36.
Bertsekas, D. P., and Tsitsiklis, J. N. (1996). Neuro-Dynamic
Programming. Athena Scientific, Belmont, MA.
Crites, R. H., and Barto,
A. G. (1996). Improving elevator performance using reinforcement learning. In
Advances in Neural Information Processing Systems 9, pp. 1017-1023. MIT Press,
Cambridge, MA.
McCallum, A. K. (1995) Reinforcement Learning with
Selective Perception and Hidden State. University of Rochester PhD. thesis.
Nie, J., and Haykin, S. (1996). A dynamic channel assignment policy
through Q-learning. CRL Report 334. Communications Research Laboratory, McMaster
University, Hamilton, Ontario.
Precup, D., Sutton, R.S. (1998).
Multi-time models for temporally abstract planning. Advances in Neural
Information Processing Systems 11. MIT Press, Cambridge, MA.
Singh, S.
P., and Bertsekas, D. (1997). Reinforcement learning for dynamic channel
allocation in cellular telephone systems. In Advances in Neural Information
Processing Systems 10, pp. 974-980. MIT Press, Cambridge, MA.
Sutton, R.
S. (1988). Learning to predict by the methods of temporal differences. Machine
Learning, 3:9-44.
Sutton, R. S., and Barto, A. G. (1998). Reinforcement
Learning: An Introduction. MIT Press, Cambridge, MA.
Sutton, R. S.,
Precup, D., Singh, S. (1998). Between MDPs and semi-MDPs: Learning, planning,
and representing knowledge at multiple temporal scales. Technical Report 98-74,
Department of Computer Science, University of Massachusetts.
Tesauro, G.
J. (1995). Temporal difference learning and TD-Gammon. Communications of the
ACM, 38:58-68.
Watkins, C. J. C. H. (1989). Learning from Delayed
Rewards. Ph.D. thesis, Cambridge University.
Zhang, W., and Dietterich,
T. G. (1996). High-performance job-shop scheduling with a time-delay TD network.
In Advances in Neural Information Processing Systems 9, pp. 1024-1030. MIT
Press, Cambridge, MA.