78778 - Intelligent Systems M

Course Unit Page

  • Teacher Michela Milano

  • Credits 8

  • SSD ING-INF/05

  • Teaching Mode Traditional lectures

  • Language English

  • Campus of Bologna

  • Degree Programme Second cycle degree programme (LM) in Computer Engineering (cod. 5826)

Academic Year 2022/2023

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

PLANNING

  • Non-linear planning
  • Conditional planning
  • Graph-based planning
  • Planning for robotics

MACHINE LEARNING: symbolic and sub-symbolic approaches

  • Decision trees - random forests
  • Neural networks
  • Bayesian approaches
  • Inductive logic programming

OPTIMIZATION

  • Constraint Programming and Global constraints
  • Search strategies
  • Applications

SWARM INTELLIGENCE

  • Ant colony
  • Bee Colony
  • Particle Swarm Optimization

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