TDDC17 Artificial Intelligence

Lectures

The schedule and content for the 2026 Fall Lectures is updated.

2026 slides will be posted incrementally, before each lecture, old slides still available.

Last Changed: 22 August, 2026 10:40

Week 36

• Mon. 31/8 10-12 !1
  • Lecture 1: Course Introduction, Big Ideas in AI (Lecturer: Fredrik Heintz)
  • Hour 1: What can AI do? What is AI?
  • Hour 2: What does AI consist of? The Intelligent Agent Paradigm.
  • Reading: ch1, ch2, ch27[27.1-2]. Turing article.
  • Slides: Le1 (2025)
• Thu. 3/9 08-10 A1
  • Lecture 2: Search I (Lecturer: Fredrik Heintz)
  • Hour 1: The physical symbol system hypothesis. Introduction to search.
  • Hour 2: Uninformed search.
  • Reading: ch3:[3.1-3.4], Newell and Simon article.
  • Slides: Le2 (2025)

Week 37

• Tue. 8/9 13-15 A1
  • Lecture 3: Search II (Lecturer: Fredrik Heintz)
  • Hour 1: Informed Search, Heuristic Search
  • Hour 2: Beyond Classical Search, Adverserial Search
  • Reading: ch3:[3.5-3.6], ch4:[4.1], ch6: [6.1-6.4]
  • Slides: Le3 (2025)
• Thu. 10/9 8-10 A1
  • Lecture 4: Constraint Satisfaction (Lecturer: Fredrik Heintz)
  • Constraint Satisfaction Problems (2025)
  • Backtracking and Inference (2025)
  • Reading: ch5: 5.1-5.4
• Fri. 11/9 15-17 A1
  • Lecture 5: Knowledge Representation I (Lecturer: Arnoud Lequen)
  • Propositional Logic: Syntax, Semantics, Conjunctive Normal Form (2025)
  • Reading: ch7 (7.7.3-4 not required)

Week 38

• Mon. 14/9 10-12 A2
  • Lecture 6: Knowledge Representation II (Lecturer: Arnoud Lequen)
  • Propositional Logic: Resolution, DPLL (2025)
  • Propositional Logic: Local Search (2025)
  • Reading: ch7: 7.6, ch8: 8.1-2:
• Tue. 15/9 13-15 C4
  • Lecture 7: Knowledge Representation III (Lecturer: Arnoud Lequen)
  • First-Order Logic (2025)
  • Answer Set Programming (2025)
  • Reading: ch9: 9.1, 9.3.1, 9.3.2, 9.4.2, 9.4.3,9.4.4, ch10: 10.6.1
• Fri. 18/9 15-17 A1
  • Lecture 8: Bayesian Networks (Lecturer: Fredrik Heintz)
  • Probability (2025)
  • Bayesian Networks (2025)
  • Reading: ch12, ch13: 13.1, 13.2.1

Week 39

• Mon. 21/9 10-12 C1
  • Lecture 9: Machine Learning I (Lecturer: Fredrik Heintz)
  • Hour 1: Introduction to Machine Learning
  • Hour 2: Supervised Learning, Unsupervised Learning
  • Reading: ch19: 19.1-19.4, 19.6, ch21: 21.1
  • Slides: Le9 (2025)
• Tue. 22/9 15-17 C4
  • Lecture 10: Machine Learning II (Lecturer: Fredrik Heintz)
  • Hour 1: Neural Networks, Deep Learning
  • Hour 2: Deep Generative Models
  • Reading: ch22: 22.1-22.4.1, 22.6
  • Slides: Le10 (2025)
• Fri. 25/9 15-17 A1
  • Lecture 11: Machine Learning III (Lecturer: Fredrik Heintz)
  • Reinforcement Learning
  • Reading: ch16: 16.1-2, ch23: 23.1-23.4.3
  • Slides: Le11 (2025)

Week 40

• Mon. 28/9 10-12 C1
  • Lecture 12: Planning 1 (Lecturer: Mauricio Salerno)
  • Planning Tasks (2025)
  • Abstraction Heuristics (2025)
  • Reading: ch11: 11.1, 11.2.1, 11.3.2
• Tue. 29/9 13-15 C4
  • Lecture 13: Planning 2 (Lecturer: Mauricio Salerno)
  • Delete Relaxation (2025)
  • Delete Relaxation Heuristics (2025)
• Fri. 2/10 15-17 A2
  • Lecture 14: Planning 3 (Lecturer: Mauricio Salerno)
  • Markov Decision Processes (2025)
  • Solving MDPs (2025)
  • Reading: ch16: 16.1, 16.2

Week 41

• Mon. 5/10 10-12 C4
  • Lecture 15: Trustworthy AI (Lecturer: Fredrik Heintz)
  • New lecture
• Tue. 6/10 13-15 A1
  • Lecture 16: Agentic AI (Lecturer: Fredrik Heintz)
  • New lecture
• Fri. 9/10 15-17 A1
  • Lecture 17: Physical AI (Lecturer: Mariusz Wzorek)
  • New lecture
  • Slides: Le17 (2025)

Page responsible: Fredrik Heintz
Last updated: 2026-08-22