LOGIC FOR PRACTICAL REASONING AND ARTIFICIAL INTELLIGENCE
Stampa
Anno immatricolazione
2021/2022
Anno offerta
2023/2024
Normativa
DM270
SSD
M-FIL/02 (LOGICA E FILOSOFIA DELLA SCIENZA)
Dipartimento
DIPARTIMENTO DI MATEMATICA 'FELICE CASORATI'
Corso di studio
ARTIFICIAL INTELLIGENCE
Curriculum
PERCORSO COMUNE
Anno di corso
Periodo didattico
Secondo Semestre (04/03/2024 - 18/06/2024)
Crediti
6
Ore
48 ore di attività frontale
Lingua insegnamento
INGLESE
Tipo esame
SCRITTO E ORALE CONGIUNTI
Docente
LANDES JUERGEN (titolare) - 5 CFU
KUBYSHKINA EKATERINA - 1 CFU
Prerequisiti
Students are expected to have a basic knowledge of linear algebra, vector calculus, logic and probability.
Obiettivi formativi
At the end of the course students will be able to understand and discuss the principles of logic applied to practical reasoning and AI. They will be able to analyze a problem, and to design and implement a solution. They will be familiar with important techniques in the field and will be able to use them.
Programma e contenuti
After a refresher of logic covering basic concepts of propositional and first-order logic, the course will cover a variety of topics and techniques relating to logic and AI.
Topics to be discussed are Argumentation, Belief Revision, Probabilistic Logic, Bayesian Networks, Paraconsistency (incl. Paradoxes), Inductive Logic, Philosophy of AI, modal logic and epistemic logic.
Metodi didattici
This course has two main parts: lectures and exercises.
Programming will not be part of this course.
Testi di riferimento
The course is based on a set of notes that are supplemented by a selection of articles.
Modalità verifica apprendimento
The exam consists of an interview or a written in-class-assignment in which the student will discuss the topics of the course.
Altre informazioni
Obiettivi Agenda 2030 per lo sviluppo sostenibile