Home » Laurea Magistrale » Corsi » KNOWLEDGE REPRESENTATION AND LEARNING

Laurea Magistrale

Salta il menu di secondo livello

KNOWLEDGE REPRESENTATION AND LEARNING - 6 CFU

Insegnante

Luciano Serafini

Periodo

I Anno - 2 Semestre | 01/03/2021 - 12/06/2021

Ore: 48 (48 lezione)

Torna su ▲

Prerequisiti

Suggested basic knowledge of logics and statistics.

Conoscenze e abilità da acquisire

Introduce the students to the principles for logics for knowledge representation and reasoning, statistical relational learning, and the combination of the two in order to build system for learning and reasoning in hybrid domains.

Modalità di esame

Final examination based on: written examination or project development.

Criteri di valutazione

Critical knowledge of the course topics. Ability to present and apply the studied material

contenuti

(A) Logics for knowledge representation:
(A.i) introduction to propositional logics, syntax, semantics, decision procedure. Satisfiability, weighted satisfiability, and best satisfiability.
(A.ii) First order logics, syntax, semantics, resolution and unification.
(A.iii) Fuzzy logics, syntax, semantics, and reasoning.

(B) statistical relational learning:
(B.i) Graphical models
(B,ii) Markov Logic Networks
(B.iii) Probabilistic prolog,
(B.iii) Logic Tensor Networks

Attività di apprendimento previste e metodologie di insegnamento

Lectures supported by exercises and lab

Eventuali indicazioni sui materiali di studio

Lecture notes and slides for the part not covered by textbooks will be provided.

Testi di riferimento

Torna su ▲