Studying at the University of Verona
Here you can find information on the organisational aspects of the Programme, lecture timetables, learning activities and useful contact details for your time at the University, from enrolment to graduation.
Academic calendar
The academic calendar shows the deadlines and scheduled events that are relevant to students, teaching and technical-administrative staff of the University. Public holidays and University closures are also indicated. The academic year normally begins on 1 October each year and ends on 30 September of the following year.
Course calendar
The Academic Calendar sets out the degree programme lecture and exam timetables, as well as the relevant university closure dates..
Period | From | To |
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I semestre | Oct 1, 2018 | Jan 31, 2019 |
II semestre | Mar 4, 2019 | Jun 14, 2019 |
Session | From | To |
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Sessione invernale d'esame | Feb 1, 2019 | Feb 28, 2019 |
Sessione estiva d'esame | Jun 17, 2019 | Jul 31, 2019 |
Sessione autunnale d'esame | Sep 2, 2019 | Sep 30, 2019 |
Session | From | To |
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Sessione Estiva | Jul 18, 2019 | Jul 18, 2019 |
Sessione Autunnale | Oct 17, 2019 | Oct 17, 2019 |
Sessione Invernale | Mar 18, 2020 | Mar 18, 2020 |
Period | From | To |
---|---|---|
Sospensione dell'attività didattica | Nov 2, 2018 | Nov 3, 2018 |
Vacanze di Natale | Dec 24, 2018 | Jan 6, 2019 |
Vacanze di Pasqua | Apr 19, 2019 | Apr 28, 2019 |
Festa del Santo Patrono | May 21, 2019 | May 21, 2019 |
Vacanze estive | Aug 5, 2019 | Aug 18, 2019 |
Exam calendar
Exam dates and rounds are managed by the relevant Science and Engineering Teaching and Student Services Unit.
To view all the exam sessions available, please use the Exam dashboard on ESSE3.
If you forgot your login details or have problems logging in, please contact the relevant IT HelpDesk, or check the login details recovery web page.
Should you have any doubts or questions, please check the Enrollment FAQs
Academic staff
Study Plan
The Study Plan includes all modules, teaching and learning activities that each student will need to undertake during their time at the University.
Please select your Study Plan based on your enrollment year.
1° Year
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2° Year activated in the A.Y. 2019/2020
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Legend | Type of training activity (TTA)
TAF (Type of Educational Activity) All courses and activities are classified into different types of educational activities, indicated by a letter.
Foundations of Computing - INTELLIGENZA ARTIFICIALE (2018/2019)
Teaching code
4S02789
Credits
6
Coordinator
Not yet assigned
Language
Italian
Scientific Disciplinary Sector (SSD)
INF/01 - INFORMATICS
To show the organization of the course that includes this module, follow this link: Course organization
The teaching is organized as follows:
Teoria
Laboratorio
Learning outcomes
The class presents the main techniques for problem solving, based on the central paradigm of symbolic and probabilistic representations. The objective is to provide the students with the ability to design, apply and evaluate algorithms for difficult problems, meaning that their mechanical solution captures aspects of artificial intelligence or computational rationality.
At the end of the course the student must demonstrate to know and understand the main techniques for state space search, to understand the fundamental concepts related to constrained networks and to know the basic concepts related to probabilistic reasoning and reinforcement learning.
This knowledge will allow the student to: i) apply the state space search techniques to problems of different nature; ii) apply the main solution algorithms for constrained networks both in the context of satisfiability and optimization; iii) use the main solution techniques related to probabilistic reasoning, with particular emphasis on Bayesian networks, Markov decision processes and reinforcement learning.
At the end of the course the student will be able to: i) choose the most appropriate solution technique for different problems; ii) continue independently the studies in Artificial Intelligence, deepening the topics covered in class, both on other texts and on scientific publications.
Program
Problem solving as search in a state space; un-informed search procedures; heuristic search procedures; adversarial search.
Problem solving based on constraint processing (satisfaction and optimization); Solution techniques based on search (Backtracking, Branch and Bound) and inference (Join Tree Clustering, Bucket Elimination);
Intelligent agents: multi-agent systems, coordination.
Probabilistic reasoning: i) Bayesian networks (definitions, main concepts and inference methods); ii) Markov decision processes (definitions and main solution techniques); iii) reinforcement learning (basic concepts and solution
techniques, e.g. Q-Learning).
Implementing (through assisted software development) the main solution techniques presented during the course related to state space search and probabilistic reasoning.
Students can find teaching material and further information on this course at this link: http://profs.sci.univr.it/~farinelli/courses/ia/ia.html
Bibliography
Activity | Author | Title | Publishing house | Year | ISBN | Notes |
---|---|---|---|---|---|---|
Teoria | Stuart Russell, Peter Norvig | Artificial Intelligence: A Modern Approach (Edizione 2) | Prentice Hall | 2003 | 0137903952 | |
Teoria | Rina Dechter | Constraint Processing (Edizione 1) | Morgan Kaufmann | 2003 | ISBN 978-1-55860-890-0 | |
Teoria | Richard S. Satto and Andrew G. Barto | Reinforcement Learning: an introduction | MIT press | 1998 | ISBN 0-262-19398-1 |
Examination Methods
The final grade for the IA module is achieved with a written test and a test in the programming laboratory. The written test requires the student to apply the algorithms and the methodologies studied during the course. The test in the programming laboratory aims at evaluating the software produced by the students during the laboratory course.
Type D and Type F activities
Documents and news
- PIANO DIDATTICO LM-18 LM-32 (octet-stream, it, 17 KB, 21/09/18)
Modules not yet included
Career prospects
Module/Programme news
News for students
There you will find information, resources and services useful during your time at the University (Student’s exam record, your study plan on ESSE3, Distance Learning courses, university email account, office forms, administrative procedures, etc.). You can log into MyUnivr with your GIA login details: only in this way will you be able to receive notification of all the notices from your teachers and your secretariat via email and soon also via the Univr app.
Graduation
Deadlines and administrative fulfilments
For deadlines, administrative fulfilments and notices on graduation sessions, please refer to the Graduation Sessions - Science and Engineering service.
Need to activate a thesis internship
For thesis-related internships, it is not always necessary to activate an internship through the Internship Office. For further information, please consult the dedicated document, which can be found in the 'Documents' section of the Internships and work orientation - Science e Engineering service.
Final examination regulations
List of theses and work experience proposals
Attendance
As stated in the Teaching Regulations for the A.Y. 2022/2023, attendance at the course of study is not mandatory.