Artificial Intelligence

University of Cagliari

Academic year: 2024-2025

Instructors: Prof. Giorgio Fumera, Dr. Ambra Demontis

MSc programs in:

• Computer Engineering, Cybersecurity and Artificial Intelligence (course description)
• Electronic Engineering (course description)
• Internet Engineering (course description)

Lecture schedule

• Tue, Oct. 1: Introduction to the Artificial Intelligence field. Graph search algorithms
• Wed, Oct. 2: Graph search algorithms
• Thu, Oct. 3: Machine learning
• Tue, Oct. 8: Graph search algorithms
• Wed, Oct. 9: Graph search algorithms
• Thu, Oct. 10: Machine Learning
• Tue, Oct. 15: Graph search algorithms
• Wed, Oct. 16: Logical languages for knowledge representation and reasoning
• Thu, Oct. 17: Machine Learning
• Tue, Oct. 22: Logical languages for knowledge representation and reasoning
• Wed, Oct. 23: Logical languages for knowledge representation and reasoning
• Thu, Oct. 24: Machine Learning
• Tue, Oct. 29: Logical languages for knowledge representation and reasoning
• Tue, Nov. 5: Machine Learning
• Wed, Nov. 6: Logical languages for knowledge representation and reasoning
• Tue, Nov. 12: Logical languages for knowledge representation and reasoning
• Wed, Nov. 13: Uncertain knowledge representation and reasoning: Bayesian networks
• Thu, Nov. 14: Uncertain knowledge representation and reasoning: Bayesian networks
• Tue, Nov. 19: Machine Learning
• Wed, Nov. 20: Uncertain knowledge representation and reasoning: Bayesian networks
• Thu, Nov. 21: Machine Learning
• Tue, Nov. 26: Machine Learning
• Wed, Nov. 27: Machine Learning
• Tue, Dec. 3: Machine Learning
• Wed, Dec. 4: Machine Learning
• Thu, Dec. 5: Machine Learning
• Tue, Dec. 10: Machine Learning
• Wed, Dec. 11: Uncertain knowledge representation and reasoning: Bayesian networks
• Tue, Dec. 17 (exceptionaly from 15 to 18): Machine Learning
• Wed, Dec. 18: Uncertain knowledge representation and reasoning: Bayesian networks
• Thu, Nov. 19 (exceptionaly from 11 to 14): Machine Learning

Lecture slides

Introduction to AI

Part I – Problem-solving, Knowledge and Reasoning (G. Fumera)

1. Graph Search Problems
2. Knowledge Representation and Reasoning: Logical Languages (updated on Oct. 29, 2024)
3. Uncertain Knowledge Representation and Reasoning: Bayesian Networks (updated on Dec. 18, 2024)

Part II – Machine Learning (A. Demontis)

1. Introduction to Machine Learning
2. Decision Trees
3. Performance Evaluation
4. Neural Networks
5. Ensemble Methods (soon available)

Exercises

1. Graph Search Problems
2. Logical Languages for Knowledge Representation and Reasoning (updated on Dec. 15, 2024: correction to the solution of exercise 2(b) on propositional logic)
3. Bayesian Networks for Uncertain Knowledge Representation and Reasoning (soon available)
4. Machine Learning (soon available)

Exam dates

• Tue., Jan. 14, 14:00, Room 1
• Tue., Feb. 4, 14:00, Room 1
• Tue., Feb. 25, 14:00, Room C