| Lecture | Tutorial |
|---|---|
| Module 0 - Introduction to Artificial Intelligence | |
| 1 - Introduction to AI and Rational Agents | |
| Module 1 - Search Algorithms | |
| 2 - Blind and Uninformed Search Algorithms | 1 - Agent Design Problem |
| 3 - Informed / Heuristic Search | 2 - Agent Design Problem Implementation |
| Module 2 - Reasoning and Planning with Certainty | |
| 4 - Constraint Satisfaction Problems | 3 - Search Algorithms |
| 5 - Logic, Proposition and Inference | 4 - Constraint Satisfaction Problems |
| Module 3 - Reasoning and Planning under Certainty | |
| 6 - Probability and Decision Theory | 5 - Logic, Proposition and Inference |
| 7 - Markov Decision Processes | 6 - Markov Chains |
| 8 - MDP Approximations and Refinements | 7 - Markov Decision Processes |
| Module 4 - Learning to Act | |
| 9 - Exploration vs Exploitation, Reinforcement Learning | 8 - Monte Carlo Tree Search |
| 10 - SARSA and VFA for RL | 9 - Multi-Armed Bandits |
| 11 - Deep Reinforcement Learning | 10 - Multi-Armed Bandits Continued |
| 12 - Reasoning about Other Agents | 11 - Deep Q Networks |