Knowledge Representation and Reasoning
A.Y. 2023/2024
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: First semester
Assessment methods: Esame
Assessment result: voto verbalizzato in trentesimi
Single course
This course can be attended as a single course.
Course syllabus and organization
Single session
Lesson period
First semester
Course syllabus
- A Brief History of KR Languages
- Open-world vs. Closed-world Views
- The Representation of Concepts and Relations
- Standard Reasoning Techniques
- Dealing with Imperfect Knowledge
- Applications and Limitations of KR Methods
- Open-world vs. Closed-world Views
- The Representation of Concepts and Relations
- Standard Reasoning Techniques
- Dealing with Imperfect Knowledge
- Applications and Limitations of KR Methods
Prerequisites for admission
Basic notions of algebra, logic, and set theory
Teaching methods
The course is mainly of a theoretical nature, and is based on frontal lectures. Slides and text handouts are provided in advance of each lecture. Exercises are provided for students to measure and deepen their understanding of the topic.
Teaching Resources
- Baader et al: Introduction to Description Logics
- Other material will be provided for the specific topics covered
- Other material will be provided for the specific topics covered
Assessment methods and Criteria
The course will be evaluated through a written exam based on multiple-answer, open-answer, and exercise solving questions. The exercises and examples provided during the lecture will serve as practice for the examination.
INF/01 - INFORMATICS - University credits: 6
Lessons: 48 hours
Professor:
Penaloza Nyssen Rafael
Educational website(s)