Knowledge Representation and Reasoning
A.Y. 2024/2025
Learning objectives
The main objective of the course is to provide the students with basic understanding of (logic-based) knowledge representation and reasoning.
The course presents important knowledge representation languages, their use and limitations, and techniques and tools for reasoning over them. After completing the course, the students will be able to handle the main tools and dive deeper into the theoretical results of the area.
The course presents important knowledge representation languages, their use and limitations, and techniques and tools for reasoning over them. After completing the course, the students will be able to handle the main tools and dive deeper into the theoretical results of the area.
Expected learning outcomes
The expected learning results are:
- understand the main knowledge representation languages and their limitations
- learn to solve different reasoning tasks being aware of their complexity
- develop methods to derive logical consequences from explicit knowledge
- learn to analyse logical formulas and understand their intended meaning
- Apply logic-based knowledge representation to advanced AI applications
- understand the main knowledge representation languages and their limitations
- learn to solve different reasoning tasks being aware of their complexity
- develop methods to derive logical consequences from explicit knowledge
- learn to analyse logical formulas and understand their intended meaning
- Apply logic-based knowledge representation to advanced AI applications
Lesson period: Second semester
Assessment methods: Esame
Assessment result: voto verbalizzato in trentesimi
Single course
This course cannot be attended as a single course. Please check our list of single courses to find the ones available for enrolment.
Course syllabus and organization
Single session
Lesson period
Second semester
INF/01 - INFORMATICS - University credits: 6
Lessons: 48 hours
Professor:
Penaloza Nyssen Rafael