- 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 19, 2024 to Apr 16, 2024
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from Apr 22, 2024 to Jun 04, 2024
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
Module 2:
SWARM INTELLIGENCE
- Ant colony
- Bee Colony
- Particle Swarm Optimization
MACHINE LEARNING (symbolic and sub-symbolic approaches)
- Decision trees - random forests
- Neural networks
- Bayesian approaches
- Inductive logic programming
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