KNOWLEDGE REPRESENTATION AND REASONING - MOD. 1
Stampa
Enrollment year
2021/2022
Academic year
2021/2022
Regulations
DM270
Academic discipline
INF/01 (COMPUTER SCIENCE)
Department
DEPARTMENT OF MATHEMATICS "FELICE CASORATI"
Course
ARTIFICIAL INTELLIGENCE
Curriculum
PERCORSO COMUNE
Year of study
Period
(04/10/2021 - 17/06/2022)
ECTS
6
Lesson hours
56 lesson hours
Language
English
Activity type
WRITTEN AND ORAL TEST
Teacher
PENALOZA NYSSEN RAFAEL (titolare) - 6 ECTS
Prerequisites
Basic notions of algebra, logic, and set theory
Learning outcomes
The main objective of the course is to provide the students with basic understanding of (logic-based) knowledge representation and reasoning. With this understanding, the students will be able to handle the main tools and dive deeper into the theoretical results of the area.

The expected learning results are:
- Knowledge about the main knowledge representation languages and their limitations
- Knowledge about the usual reasoning tasks and their complexity
- Be able to derive logical consequences from explicit knowledge
- Be able to analyse logical formulas and their intended meaning
- Apply logic-based knowledge representation to advanced AI applications
Course contents
Teaching methods
The course is based on frontal lectures and exercise sessions. For the lessons, slides and text handouts will be provided. The exercises will be given in advance and solved at the classroom.
Reccomended or required readings
Assessment methods
The course will be evaluated through a written exam based on several kinds of questions. In particular, it will contain multiple-answer, open-answer, and exercise solving questions. The exercises solved during the lecture and additional examples provided during the lecture will serve as practice for the examination.
Further information
Sustainable development goals - Agenda 2030