TDDC17 Artificial Intelligence

Lectures

2025 Fall Lectures!

The schedule and content for the 2025 Fall Lectures is updated.

2025 slides will be posted incrementally, before each lecture, old slides still available.

Last Changed: 11 September, 2025 11:45

Week 36

• Tue. 2/9 15-17 C1
  • Lecture 1: Big ideas in AI (Lecturer: Fredrik Heintz)
  • Hour 1: What is AI? Why is AI important?
  • Hour 2: The Intelligent Agent Paradigm. Philosophical and mathematical roots.
  • Reading: ch1, ch2, ch27[27.1-2]. Turing article.
  • Slides: Le1 (2025)
• Thu. 4/9 08-10 C1
  • 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. 9/9 13-15 C1
  • Lecture 3: Search II (Lecturer: Fredrik Heintz)
  • Hour 1: Informed 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. 11/9 8-10 C1
  • Lecture 3: Constraint Satisfaction (Lecturer: Fredrik Heintz)
  • Constraint Satisfaction Problems (2025)
  • Backtracking and Inference (2025)
  • Reading: ch5: 5.1-5.4
• Fri. 12/9 15-17 C1
  • Lecture 5: Knowledge Representation I (Lecturer: Jendrik Seipp)
  • Propositional Logic: Syntax, Semantics, Conjunctive Normal Form
  • Reading: ch7 (7.7.3-4 not required)

Week 38

• Mon. 15/9 10-12 C1
  • Lecture 6: Knowledge Representation II (Lecturer: Jendrik Seipp)
  • Propositional Logic: Resolution, DPLL
  • Propositional Logic: Local Search
  • Reading: ch7: 7.6, ch8: 8.1-2:
• Tue. 16/9 13-15 C1
  • Lecture 7: Knowledge Representation III (Lecturer: Jendrik Seipp)
  • First-Order Logic
  • Answer Set Programming
  • Reading: ch9: 9.1, 9.3.1, 9.3.2, 9.4.2, 9.4.3,9.4.4, ch10: 10.6.1
• Fri. 19/9 15-17 C1
  • Lecture 8: Bayesian Networks (Lecturer: Fredrik Heintz)
  • Probability
  • Bayesian Networks
  • Reading: ch12, ch13: 13.1, 13.2.1

Week 39

• Mon. 22/9 10-12 C1
  • Lecture 9: Machine Learning I (Lecturer: Fredrik Heintz)
  • Hour 1: Introduction to Machine Learning
  • Hour 2: Supervised Learning
  • Reading: ch19: 19.1-19.4, 19.6, ch21: 21.1
  • Slides: Le9 (2024)
• Tue. 23/9 15-17 C1
  • Lecture 10: Machine Learning II (Lecturer: Fredrik Heintz)
  • Hour 1: Neural Networks
  • Hour 2: Deep Generative Models
  • Reading: ch22: 22.1-22.4.1, 22.6
  • Slides: Le10 (2024)
• Fri. 26/9 15-17 C1
  • Lecture 11: Machine Learning III (Lecturer: Fredrik Heintz)
  • Reinforcement Learning
  • Reading: ch16: 16.1-2, ch23: 23.1-23.4.3
  • Slides: Le11 (2024)

Week 40

• Mon. 29/9 10-12 C1
  • Lecture 12: Planning 1 (Lecturer: Jendrik Seipp)
  • Planning Tasks
  • Abstraction Heuristics
  • Reading: ch11: 11.1, 11.2.1, 11.3.2
• Tue. 30/9 13-15 C1
  • Lecture 13: Planning 2 (Lecturer: Jendrik Seipp)
  • Delete Relaxation
  • Delete Relaxation Heuristics
• Fri. 3/10 15-17 C1
  • Lecture 14: Planning 3 (Lecturer: Jendrik Seipp)
  • Markov Decision Processes
  • Solving MDPs
  • Reading: ch16: 16.1, 16.2

Week 41

• Mon. 6/10 10-12 C1
  • Lecture 15: Robotics/Perception I (Lecturer: Piotr Rudol)
  • Reading: Chapt. 25
  • Slides: Le15
• Tue. 7/10 13-15 C1
  • Lecture 16: Robotics/Perception II (Lecturer: Mariusz Wzorek)
  • Reading: Chap 26
  • Slides: Le16
• Fri. 10/10 15-17 C1
  • Lecture 17: Course Summary and Discussion (Lecturer: Fredrik Heintz)
  • Slides: Le17 (2024)

Page responsible: Fredrik Heintz
Last updated: 2025-09-11