Learning objectives
An introduction to symbolic and subsymbolic artificial intelligence
Rational agents
Methods for developing an intelligent system.
The knowledge of useful tools for the analysis and development of a process
data analytics
Prerequisites
No propedeutic courses. However, Students should have knowledge of
programming (especially python).
Course unit content
1. Introduction
2 Birth of AI
3 The agents
4 Problem solving and the search for a solution
5 Adversarial searches
6 The rational agent
5 Formal logic as a language for developing intelligent systems
6 Propositional logic
7 First order logic outline
8 introduction to subsymbolic intelligence
9 Notes on Machine Learning
Full programme
1 Introduction (2 hours)
2 Birth of AI (2 hours)
3 The agents (4 hours)
4 Problem solving and finding a solution (6 hours)
-solution space-
blind and informed search strategies
5 Adversarial searches (8 hours)
-Games
-the minimax algorithm
-the alphabet pruning algorithm
-development of agents for classic Ai games
5 The rational agent and the logical agent (2 hours)
6 Formal logic as a language for developing intelligent systems (6 hours)
- Boolean logic
-inference in Boolean logic
7 first order logic (8 hours)
- predicate logic
-formalization of a problem in predicate logic
-examples of logical systems
- hints of logical planning
-structured planning
-continuous planning
8 introduction to subsymbolic intelligence (2 hours)
9 Notes on Machine Learning (8 hours)
- the learning phase
-decision trees
- hints of neural networks
Bibliography
Material provided in class
RUSSELL, Stuart J.; NORVIG, Peter. Intelligenza artificiale. Un approccio moderno. Pearson Italia Spa, 2005.
Teaching methods
Lectures and laboratory exercises.
The lectures will cover the theoretical aspects of the course subjects.
Practical exercises related to real problems will be carried out in
laboratory
Assessment methods and criteria
The exam consists of a written test with theory and practice questions.
There is a mid-term test.
Other information
Course notes and teaching materials will be distributed during the course
in electronic form.
2030 agenda goals for sustainable development
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