Unit KNOWLEDGE REPRESENTATION AND AUTOMATED REASONING
- Course
- Informatics
- Study-unit Code
- A002080
- Curriculum
- Artificial intelligence
- Teacher
- Stefano Bistarelli
- Teachers
-
- Stefano Bistarelli
- Hours
- 42 ore - Stefano Bistarelli
- CFU
- 6
- Course Regulation
- Coorte 2022
- Offered
- 2023/24
- Learning activities
- Caratterizzante
- Area
- Discipline informatiche
- Academic discipline
- INF/01
- Type of study-unit
- Obbligatorio (Required)
- Type of learning activities
- Attività formativa monodisciplinare
- Language of instruction
- Italian
- Contents
- Introduction to the area of knowledge representation with insights in the field of constraint programming, argomentation and rule based programming (drools).
- Reference texts
- hand-notes given by the teacher, and books suggested during the lessons
- Educational objectives
- Knowing and understanding of the basics of constraint programming, argumentation and rule based programming (drools).
Acquire skills to implement a project using Java and drools;
Having the ability to analyze a problem of constraints with the techniques described in class. - Prerequisites
- Knowledge of language and tools for Java programming (essential)
Knowledge of JavaScript language and Node.JS environment (important)
Knowledge of HTML and CSS (useful)
Have successfully passed the examination of Artificial Intelligence (useful) - Teaching methods
- face-to-face and Practical training
- Other information
- Frequency of the lessons is strongly suggested
- Learning verification modality
- The examination consist of a discussion of a practical project in Java that use part of the program of the course, and an oral examination (open-stimulus-response) of an average duration of 20 minutes on the remaining part of the program of the course. The purpose of the examination is to highlight the presentation skills of the student, his ability to use appropriate techniques and to highlight the deepening of the study.
On the student's request the examination can 'be in English. - Extended program
- Introduction to the course, examples of problems with constraints.
Basics of programming with constraints.
Some complete solvers.
Notions of local consistency.
Some incomplete solvers.
Constraint propagation algorithms.
Research methods in the solution space.
Arguments of advanced constraint programming:
- Soft constraints
- bipolar constraints
- constraints with uncertainty
- argumentation
- rule based programming (drools)