Difference between revisions of "SC:SC2012"
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*[http://www.abo.fi/~rfuller/fuzs.html Robert Fuller's page on Fuzzy Systems] | *[http://www.abo.fi/~rfuller/fuzs.html Robert Fuller's page on Fuzzy Systems] | ||
*TUTORIALS | *TUTORIALS | ||
| − | **Tutorial on Fuzzy Systems | + | **[http://www.seattlerobotics.org/encoder/Mar98/fuz/flindex.html Tutorial on Fuzzy Systems] |
| − | **Tutorial on Fuzzy Logic (by J. Jantzen) | + | **[http://www.iau.dtu.dk/~jj/pubs/logic.pdf Tutorial on Fuzzy Logic (by J. Jantzen)] |
| − | **Tutorial on Fuzzy Logic (by J. Brule) | + | **[http://www.austinlinks.com/Fuzzy/tutorial.html Tutorial on Fuzzy Logic (by J. Brule)] |
*BOOKS | *BOOKS | ||
**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) | **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) | ||
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**A. Sangalli, The Importance of Being Fuzzy, Princeton University Press | **A. Sangalli, The Importance of Being Fuzzy, Princeton University Press | ||
*DEVELOPMENT TOOLS | *DEVELOPMENT TOOLS | ||
| − | **XFuzzy - a set of free tools to develop fuzzy systems | + | **[http://www2.imse-cnm.csic.es/Xfuzzy/ XFuzzy - a set of free tools to develop fuzzy systems] |
| − | **FuzzyCLIPS - an extension of the NASA-developed CLIPS, a tool to implement AI systems | + | **[http://en.wikipedia.org/wiki/FuzzyCLIPS FuzzyCLIPS - an extension of the NASA-developed CLIPS, a tool to implement AI systems] |
**Tools to develop Fuzzy systems are included in Matlab and many other modeling and applicative tools. | **Tools to develop Fuzzy systems are included in Matlab and many other modeling and applicative tools. | ||
===Neural Networks=== | ===Neural Networks=== | ||
| − | *Collecton of resources about NN | + | *[http://www.makhfi.com/resources.htm Collecton of resources about NN] |
*TUTORIALS | *TUTORIALS | ||
| − | **Tutorial by Christos Stergiou and Dimitrios Siganos | + | **[http://www.doc.ic.ac.uk/~nd/surprise_96/journal/vol4/cs11/report.html Tutorial by Christos Stergiou and Dimitrios Siganos] |
*BOOKS | *BOOKS | ||
**C. Bishop, Neural Networks and Pattern Recognition, Oxford University Press, 1995 | **C. Bishop, Neural Networks and Pattern Recognition, Oxford University Press, 1995 | ||
*DEVELOPMENT TOOLS | *DEVELOPMENT TOOLS | ||
| − | **Tools to develop NN are included in many packages like Matlab and WEKA. A list of SW is available from http://www.makhfi.com/tools.htm | + | **Tools to develop NN are included in many packages like Matlab and [http://www.makhfi.com/tools.htm%20target= WEKA]. A list of SW is available from [http://www.makhfi.com/tools.htm http://www.makhfi.com/tools.htm] |
===Genetic Algorithms=== | ===Genetic Algorithms=== | ||
| − | *Portal for GA | + | *[http://www.geneticprogramming.com/ga/index.htm Portal for GA] |
| − | *The Illinois Genetic Algorithms Laboratory | + | *[http://www.illigal.uiuc.edu/web/ The Illinois Genetic Algorithms Laboratory] |
*TUTORIALS | *TUTORIALS | ||
| − | **Tutorial and demos by Marek Obitko | + | **[http://www.obitko.com/tutorials/genetic-algorithms/index.php Tutorial and demos by Marek Obitko] |
*BOOKS | *BOOKS | ||
**M. Mitchell. An Introduction to Genetic Algorithms. MIT Press. | **M. Mitchell. An Introduction to Genetic Algorithms. MIT Press. | ||
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===Reinforcement Learning=== | ===Reinforcement Learning=== | ||
| − | *Portal for RL | + | *[http://www-anw.cs.umass.edu/rlr/ Portal for RL] |
| − | *Sutton's Lab at University of Alberta. | + | *[http://rlai.cs.ualberta.ca/RLAI/rlai.html Sutton's Lab at University of Alberta.] |
*BOOKS | *BOOKS | ||
| − | **R. Sutton, A. G. Barto. Reinforcement Learning: an introduction. Addison-Wesley. (http://webdocs.cs.ualberta.ca/~sutton/book/the-book.html) | + | **R. Sutton, A. G. Barto. Reinforcement Learning: an introduction. Addison-Wesley. ([http://webdocs.cs.ualberta.ca/~sutton/book/the-book.html http://webdocs.cs.ualberta.ca/~sutton/book/the-book.html]) |
== Course Evaluation == | == Course Evaluation == | ||
TBC | TBC | ||
Revision as of 01:42, 8 November 2011
This is a description page for the PhD course on SC2012.
Contents
Course Aim & Organization
Soft Computing includes technologies (Fuzzy Systems, Neural Networks, Stochastic Algorithms , Bayesian Networks, ...) to model complex systems and offer a powerful tool both for research and companies in different, rapidly growing application areas, such as, for instance: data analysis, automatic control, modeling of artificial and natural phoenomena, modeling of behaviors (e.g., of users), decision support. The course will introduce rigorously the fundamentals of the different modeling approaches, will put in evidence the application possibilities, by comparing different models, examples and application cases, will describe how to design systems based on these technologies. No specific background is required. In past editions the course has been followed by people with many different backgrounds among which: all engineering specialties, biology, vulcanology, architecture.
Teachers
The course will be held by:
Course Schedule
Please consider this schedule as tentative ... The course will start in September 2012, details about lecture time will be available soon
In the following you find the detailed schedule for the course and the rooms booked for it. In brackets you find also the lecturer for each specific topic.
- 12/09/2012: Fuzzy Logic (4h by Andrea Bonarini)
- 14/09/2012: Fuzzy Logic (4h by Andrea Bonarini)
- 17/09/2012: Feed Forwards Neural Networks (4h by Matteo Matteucci)
- 19/09/2012: Feed Forwards Neural Networks (4h by Matteo Matteucci)
- 21/09/2012: Genetic Algorithms (4h by Andrea Bonarini)
- 24/09/2012: Bayesian Networks (4h by Matteo Matteucci)
- 26/09/2012: Estimation of Distribution Algorithms (4h by Matteo Matteucci)
- 28/09/2012: Reinforcement Learning (4h by Andrea Bonarini)
Course Material & Referencies
The following is some suggested material to follow the course lectures organized by topic.
Course Slides
TBC
Fuzzy Systems
- Robert Fuller's page on Fuzzy Systems
- TUTORIALS
- BOOKS
- 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)
- B. Kosko. Il Fuzzy pensiero. Baldini e Castoldi. (In English: Fuzzy Thinking. Hyperion Press)
- A. Sangalli, The Importance of Being Fuzzy, Princeton University Press
- DEVELOPMENT TOOLS
- XFuzzy - a set of free tools to develop fuzzy systems
- FuzzyCLIPS - an extension of the NASA-developed CLIPS, a tool to implement AI systems
- Tools to develop Fuzzy systems are included in Matlab and many other modeling and applicative tools.
Neural Networks
- Collecton of resources about NN
- TUTORIALS
- BOOKS
- C. Bishop, Neural Networks and Pattern Recognition, Oxford University Press, 1995
- DEVELOPMENT TOOLS
- Tools to develop NN are included in many packages like Matlab and WEKA. A list of SW is available from http://www.makhfi.com/tools.htm
Genetic Algorithms
- Portal for GA
- The Illinois Genetic Algorithms Laboratory
- TUTORIALS
- BOOKS
- M. Mitchell. An Introduction to Genetic Algorithms. MIT Press.
Bayesian Networks
TBC
Bayesian Networks
TBC
Reinforcement Learning
- Portal for RL
- Sutton's Lab at University of Alberta.
- BOOKS
- R. Sutton, A. G. Barto. Reinforcement Learning: an introduction. Addison-Wesley. (http://webdocs.cs.ualberta.ca/~sutton/book/the-book.html)
Course Evaluation
TBC
