2020/2021

2021/2022

DM270

ING-INF/05 (SISTEMI DI ELABORAZIONE DELLE INFORMAZIONI)

DIPARTIMENTO DI INGEGNERIA INDUSTRIALE E DELL'INFORMAZIONE

COMPUTER ENGINEERING

Computer Science and Multimedia

2°

Primo Semestre (27/09/2021 - 21/01/2022)

6

45 ore di attività frontale

English

ORALE

PIASTRA MARCO (titolare) - 6 CFU

Basic mathematical skills, practical knowledge of at least one programming language.

The course follows a conceptual pathway along the fundamental principles of the discipline. It is divided into two parts: the first part is an introduction to classical formal logic, both propositional and first order, with a special focus to the aspects of automatic calculus, while the second part is an introduction to the basic principles of machine learning from a probabilistic perspective.

1) Classical logic and automated symbolic reasoning

Boolean algebras
Logical language and semantical structures: logical consequence
Deductive systems for propositional logic
Decision problems and decidability
Predicates and relations: first order logic
Semi-decidability of first order logic
First-order resolution with unification

2) Machine Learning

Logic and probability: representation or statistics?
The language of probability: representation
Bayesian inference
Graphical models and automation
Probabilistic learning
Clustering: K-means, EM algorithm, missing data.
Causal models, probabilistic and structural.
Reinforcement Learning.

Lectures (hours/year in lecture theatre): 4.5
Practical class (hours/year in lecture theatre): 0
Practicals / Workshops (hours/year in lecture theatre): 0

See the home page of the course (http://vision.unipv.it/AI) for lecture slides, suggested readings and software for the exercises.

The final exam is an interview about the theory, together with the discussion of practical activities shown during lessons.