Advanced Logic

A.Y. 2024/2025
9
Max ECTS
60
Overall hours
SSD
MAT/01
Language
English
Learning objectives
The course aims to provide students with an overview of the most important formal systems for practical reasoning that have been put forward as extensions of classical logic. Those have a long-standing interest which has been much revived owin to the problem of endowing artificial intelligence agents with the ability to represent knowledge and reason with it.

More specifically, students will acquire a basic knowledge of the following topics:

- the agent-based view of logical consequence

- advanced classical logical tools

- qualitative representation of information and uncertanty

- non monotonic reasoning

The acquired knowledge will be fruitfully employed in teaching, and in all activities requiring a variety of reasoning tools that are more powerful than elementary logic. In addition the acquired knowledge will be very useful in understanding the core problems arising in the representation of knowledge and reasoning in artificial intelligence.
Expected learning outcomes
Knowledge and understanding:
- knowledge of the foundations of non-monotonic reasoning;
- knowledge of the main extensions of, and alternatives to classical logic.
- knowledge of the most recent investigations into the relationship between logic and information.
Ability to apply knowledge and understanding

At the end of the course students are expected to be able to apply the acquired knowledge in order to:
- read and understand original scientific contributions in the field of logic;
- analyze and solve scientific, philosophical and practical problems that do not admit of natural solutions in terms of standard logic.
Single course

This course can be attended as a single course.

Course syllabus and organization

Single session

Responsible
Lesson period
Second semester
Course syllabus
The aim of the course is to provide students with tools and methods from practical logic, with a particular focus on knowledge representation and reasoning in artificial intelligence.
Prerequisites for admission
Logical Methods
Teaching methods
Frontal and flipped lectures and assignments. The approach will be problem-oriented and students will be trained to learn by solving basic problems and exercises.
Assessment methods and Criteria
The exam is written and marked as follows:

- End of course project: 50% of the final grade
- Exam (online on Moodle based on closed and open questions): 50% of the final grade.
MAT/01 - MATHEMATICAL LOGIC - University credits: 9
Lessons: 60 hours
Professor: Hosni Hykel
Educational website(s)
Professor(s)
Reception:
Friday 8:30-11:30
Second Floor, Cortile Ghiacchiaia. Please email me to secure your slot.