|
Mandatory course of second year of the Master Degree in Computer Engineering. |
|
The course has the objective to describe methodologies of the artificial intelligence. In particular, will be discussed the concept of intelligent agent, knowledge representation, inference, deduction and machine learning. |
|
The course gives 9 credits and it is composed of 20 hours of video lectures. Video lectures present the following concepts:
-
Artificial Intelligence. Introduction
-
Intelligent Agents
-
Searching
-
Informed search
-
Constraints satisfaction problems
-
Propositional Logic
-
First Order Logic
-
Inference in First Order Logic
-
Planning
-
Planning in the real world
-
Quantifying uncertainty
-
Bayesian Networks
-
Probabilistic reasoning over time
-
Making simple decisions
-
Complex decision making. First part
-
Complex decision making. Second part
-
Learning & decision trees
-
Regression and classification. First part
-
Regression and classification. Second part
-
Learning with knowledge & statistical learning
|
S. J. Russell, P. Norvig, “Artificial Intelligence. A Modern Approach.”, Pearson, Milano
T. Mitchell - "Machine Learning"
S. Haykin, “Neural Networks - A comprehensive foundation”, Prentice-Hall |
|
During the lectures there are several exercises to be done at home. |
|
Professor/Tutor responsible for teaching
|