Lesson slides are usually published before the corresponding lesson.

NB: The documents on this site are in PDF. To read them, you can use Acrobat Reader

We kindly invite anyone finding errors or imprecisions, or whishing to share any comment and suggestion, to contact the teachers by e-mail or at the lesson.

Here is the list of reference books for this course. You are advised to work on them, and not only on the slides .

• T. Ross, Fuzzy Logic with Engineering Applications, Third Edition, Wiley, 2010 (in alternative, only for Italian Students: A. G. Pizzaleo. Fuzzy Logic: come insegneremo alle macchine a ragionare da uomini. Castelvecchi, Roma)
• C. Bishop, Neural Networks and Pattern Recognition, Oxford University Press, 1995
• R.G. Cowell A.P. Dawid, S.L. Lauritzen and D.J. Spiegelhalter, Probabilistic Networks and Expert Systems, Springer-Verlag, 1999.
• F. Karray, C. De Silva, Soft Computing and Intelligent Systems Design: Theory, Tools, and Applications, Addison-Wesley Publishing, 2004
• R. Sutton, A. G. Barto. Reinforcement Learning: an introduction (http://webdocs.cs.ualberta.ca/~sutton/book/the-book.html)

Here is a list of books suggested for further readings:

• T. Mitchell. Machine Learning. McGraw Hill
• M. Mitchell. An Introduction to Genetic Algorithms. MIT Press.
• B. Kosko. Il Fuzzy pensiero. Baldini e Castoldi. (In English: Fuzzy Thinking. Hyperion Press)
• A. Sangalli, The Importance of Being Fuzzy, Princeton University Press

• AI Resources and Repository at Carnegie-Mellon University
• NeuroNet: european network of excellence on Neural Networks
• ERUDIT: european network of excellence on Fuzzy Systems
• List of links about Neural Networks and Fuzzy Systems
• Neural Network resources
• Robert Fuller's page on Fuzzy Systems
• Un tutorial su fuzzy systems
• Un tutorial su fuzzy logic
• Sutton and Barto's Book on Reinforcement Learning The same in pdf file (thanks to Roberto Forlani)
• Course and material on Reinforcement Learning
• Tutorial on Fuzzy Logic (by J. Brule)
• Tutorial on Neural Networks (by D. Anderson)
• Tutorial on Genetic Algorithms (by M. Ramsey)
• Resources on Fuzzy Systems
• Resources on Neural Networks
• Resources on Genetic Algorithms
• Resources on Soft Computing
• Resources on Intelligent Systems
• Reinforcement Learning Resources at RL.AI
• Rich Sutton's home page (Reinforcement Learning Resources)
• Reinforcement Learning resources at University of Massachussets at Amherst
• Tutorial on bayesian networks