- Docente: Michela Milano
- Credits: 8
- SSD: ING-INF/05
- Language: English
- Moduli: Michela Milano (Modulo 1) Allegra De Filippo (Modulo 2)
- Teaching Mode: Traditional lectures (Modulo 1) Traditional lectures (Modulo 2)
- Campus: Bologna
- Corso: Second cycle degree programme (LM) in Computer Engineering (cod. 5826)
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from Feb 17, 2025 to Apr 09, 2025
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from Apr 15, 2025 to Jun 10, 2025
Learning outcomes
At the end of the course the students are able to use the main AI techniques to develop tools for solving real life applications. The students are able to understand and apply a wide range of techniques such as constraint programming, symbolic and sub-symbolic machine learning techniques, planning and swarm intelligence.
Course contents
Module 1:
PLANNING
- Non-linear planning
- Conditional planning
- Graph-based planning
- Planning for robotics
OPTIMIZATION
- Constraint Programming and Global constraints
- Search strategies
- Applications
SWARM INTELLIGENCE
- Ant colony
- Bee Colony
- Particle Swarm Optimization
Module 2:
MACHINE LEARNING
(symbolic and sub-symbolic approaches)
- Decision trees - random forests
- Neural networks
- Bayesian approaches
- Inductive logic programming
DEEP LEARNING
Readings/Bibliography
E. Rich, K. Knight: "Intelligenza Artificiale", McGraw Hill, Seconda Edizione 1992.
E. Charniak, D. McDermott, "Introduzione all'Intelligenza Artificiale", Masson, 1988.
M.Ginsberg: "Essentials of Artificial Intelligence", Morgan Kaufman,1993.
P. H. Winston: "Artificial Intelligence: Third Edition", Addison-Wesley, 1992.
Teaching methods
Lectures and laboratory exercises
Assessment methods
Written exam
Teaching tools
Slides
lab exercises
Office hours
See the website of Michela Milano
See the website of Allegra De Filippo
SDGs
This teaching activity contributes to the achievement of the Sustainable Development Goals of the UN 2030 Agenda.