The course aims to introduce students to the techniques and technologies designed to reproduce smart behaviours on the computer, typical of living beings, with particular attention to the knowledge engineering and machine learning techniques.
Knowledge and understanding
Specifically the course aims to illustrate
- the main techniques of knowledge representation used in Artificial Intelligence,
- the methodologies to formulate well-defined problems and solutions
- the management of (certain or uncertain) knowledge through logic and reasoning
- some of the most important of Machine Learning methods
- some aspects of the Semantic Web
Applying knowledge and understanding
The main goal of course is to provide students with the ability to
- formulate a problem that can be solved by a logic agent
- describe and represent knowledge through the use of logic
- analyze the knowledge used in a domain and choose the method that is considered more appropriate for its management
- solve a real world problem using machine learning methods
- design a Semantic Web application
To carry out the final project the student will need to analyze the state of the art in the literature to motivate the choices that are made in the development of the task.
Lab exercises and the project can be carried out in small groups, promoting the exchange of views. In addition, the drafting of the report requires a good logical organization and clarity in reporting data and results.
The student's ability to look at things from different perspectives is stimulated by the integration of theory lessons and laboratory activities.