Materiale di supporto al corso di Sistemi Intelligenza. A.A. 2005-2006. 

Gli articoli ed i testi sono disponibili o in biblioteca o sul sito del corso. Gli articoli ed i testi di approfondimento (suggeriti, potete sceglierne altri di vostro interesse) sono in colore verde, mentre articoli e testi di riferimento sono in colore nero.

Intelligenza simbolica
•	Russell and Norvig, Artificial Intelligence, a Modern Approach, Prentice-Hall, prima edizione (Capitoli 26-27), 2003 oppure, in italiano, Russell e Norvig, Intelligenza Artificiale, Un approccio Moderno, Volume II, (Capitoli 26-27), 2005.
•	J.E: Hopcroft, Turing Machines, Scientific American, 1984.
•	http://www.neuroingegneria.com/art/Paul%20e%20Patricia%20Churchland%20-%20Può%20una%20macchina%20pensare%20/74.php
•	J. McCarthy Concepts of Logical AI Unpublished notes, 2004 http://www-formal.stanford.edu/jmc/concepts-ai.html.
•	http://www.cs.umass.edu/~immerman/cs601/turingReference.html.
•	D. Terzopoulos, Artificial Life, Communications of the ACM, agosto 1999.
•	Craig W. Reynolds, Flocks, Herds, and Schools: A Distributed Behavioral Model, Computer Graphics, Volume 21, Number 4, July 1987.
•	Bruce M. Blumberg and Tinsley A. Galyean. Multi-Level Direction of Autonomous Creatures for Real-Time Virtual Environments. Proc. Siggraph 1995.
•	C. Langton, Studying Artificial life with cellular Automata, Physica 22D, 1986.
•	R. Penrose, “La mente nuova dell’imperatore”, Edizioni Bur, pp. 56-102
•	http://www.agentlink.org/
•	http://www.turing.org.uk/turing/.
•	Bonabeau e Theraulaz, Swarm Smarts, Scientific American, 2000.
•	J. McCarthy, What is AI? Unpublished notes, 2004. http://www formal.stanford.edu/jmc/whatisai.html.
•	J. McCarthy and P. Hayes, Some Philosophical problem from the standpoint of artificial intelligence, Machine Intelligence 4, 1969. http://www-formal.stanford.edu/jmc/mcchay69.html
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•	Algoritmi Genetici
•	•	Cerveri P., Pedotti A., Borghese N.A., Combined evolution strategies for dynamic calibration of video based measurement systems IEEE Transaction on Evolutionary Computation, Volume: 5 Issue: 3, pp. 271-282, June 2001. (solamente per la parte di ottimizzazione evoluzionistica).
•	Buche, D. Schraudolph, N.N. Koumoutsakos, P., Accelerating evolutionary algorithms with Gaussian process fitness function models, IEEE Transactions on Systems, Man and Cybernetics, Part C, 35(2), pp. 183- 194, 2005.
•	Cerveri P. Pedotti A., Ferrigno G., Evolutionary optimization for robust hierarchical computation of the rotation centres of kinematical chains from reduced ranges of motion: the lower spine case. Journal of Biomechanics, 37(12), pp. 1881-1890, 2004.
•	Cerveri P., Lopomo N., Pedotti A., Ferrigno G., Derivation of centers and axes of rotation for wrist and fingers in a hand kinematic model: robust methods and reliability results, Annals of Biomedical Engineering, 33(3), pp. 402-12, 2005.
•	Goldberg D.E. (1989), Genetic Algorithms in Search, Optimization and Machine Learning, Addison Wesley Longman Inc.
•	Hansen N. and Ostermeier A., “Completely derandomized self-adaptation in evolution strategies,” Evol. Comput., vol. 9, no. 2, pp. 159-195, 2001.
•	Hansen N., Müller S. D., and Koumoutsakos P., “Reducing the time complexity of the derandomized evolution strategy with covariance matrix adaptation (CMA-ES),” Evol. Comput., vol. 11, no. 1, pp. 1-18, 2003. 
•	Holland J.H. (1975), Adaptation in Natural and Artificial Systems, Cambridge MA, MIT Press.
•	Schwefel, H.-P. (1981). Numerical optimization of computer models. Chichester: Wiley.

Sistemi fuzzy
Kosko, Neural Networks and Fuzzy Systems, Prentice Hall (Cap. 7-8).

Connessionismo e Reinforcement Learning
·	Sutton and Barto, Reinforcement Learning - An Introduction, MIT Press, 1998. Capitoli: 1 (intero), 2.1, 2.2, 2.5, 2.6, 2.7, 2.11, 3 (intero), 4 (intero), 6 (intero). Il libro si trova on-line al sito: http://www.cs.ualberta.ca/~sutton/book/the-book.html.
·	Barto, Sutton e Anderson, Neuronlike Adaptive Elements That Can Solve Difficult Learning Control Problems. IEEE Trans. Systems, Man & Cybernetics, 1983. 
·	N.A. Borghese and A. Calvi (2002), Learning to maintain upright posture: what can be learned by using Neural Network Models? 
·	L. P. Kaelbling, M. L. Littman, and A. W. Moore. Reinforcement learning: A survey. Journal of Artificial Intelligence Research, 4:237--285, 1996.
•	http://www.cs.rutgers.edu/~mlittman/topics/nips05-mdp/
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•	Reti Neurali e Modelli Parametrici
•	Hertz, Krough and Palmer, Introduction to the theory of Neural Computation, Addison Wesley, 1991 (Capitoli 1, 5.0, 5.1, 5.4, 9.0, 9.4). 
•	A.K. Jain, M.N. Murty and P.J. Flynn, "Data clustering: a review", ACM Computing Surveys, Vol. 31, No. 3, September 1999, solamente le pp. 265-290.
•	C. Bishop, Neural Networks for Pattern Recognition, Oxford University Press, 1996 (Capitolo 2, 2.1, 2.2, 2.6)
•	I. Frosio, and N. A. Borghese A new switching median filter for digital radiography. Proc. MIC 2004. 
•	Frosio I., Ferrigno G., Borghese N.A. (2006). Enhancing Digital Cephalic Radiography with Mixture Models and Local Gamma Correction. IEEE Trans. Medical Imaging. Volume 25, Issue 1, Jan. 2006 Page(s):113 - 121. 
•	J. Moody and C. Darken, Fast-learning in networks of locally-tuned processing units, Neural Computation 1(2) (1989) 281-294.
•	F. Girosi, M. Jones, T. Poggio, Prioris, Stabilizers, and Basis Functions: from regularization to radial, tensor and additive splines, A.I. Memo No. 1430, MIT, 1993.
•	Jervis and Fallside, Pole Balancing on a Real Rig using Reinforcement Learning Controller, 1992.
•	J. Moody and C.J. Darken, Fast Learning in Networks of Locally-Tuned Processing Units, Neural Computation, Vol. 1, pp. 281-294, 1989.
•	D.F. Specht, Probabilistic Neural Networks, Neural Networks, Vol. 3, pp. 109-118, 1990.
•	A.Baraldi and P.Blonda, A survey of fuzzy clustering algorithms for Pattern Recognition, Part I and II, IEEE Trans. on Systems, Man and Cybernetics, Part B, Vol. 29, No. 6, 1999.

Realtà Virtuale & Motion Capture
•	http://web.media.mit.edu/~halazar/autostereo/autostereo.html.
•	Mikic, Trivedi, Hunter, Cosman, Human Body Model Acquisition and Tracking Using Voxel Data, Int. J. Computer Vision, 53(3), 199–223, 2003.
•	F. Davide, M. Holmberg, I. Lundstrom. Virtual olfactory interfaces:electronic noses and olfactory displays. Communications Through Virtual Technology: Identity Community and Technology in the Internet Age Edited by G. Riva and F. Davide, IOS Press: Amsterdam, 2003.
•	A. Cappelli, E. Giovannetti, L’interazione uomo-robot. Proc. AIIA Workshop, 2004.