Here is a brief diary of topics discussed in classes.

Slides and coding scripts are distributed after each lecture via the Google groups mailing-list. Refer to the home page on how to subscribe.

[28/02/2025] Introduction AI

[03/03/2025] Logical Agents

[07/03/2025] State space graphs, search trees and uninformed search

[10/03/2025] Depth-First Search, Breadth-First Search, Uniform-Cost Search

[14/03/2025] Informed search: greedy search

[17/03/2025] Informed search: A*

[21/03/2025] Graph search with A* and hill climbing

[24/03/2025] Simulated annealing, beam search, genetic algorithms

[28/03/2025] Constraint Satisfaction Problems and Backtracking Search

[31/03/2025] Improving Backtracking Search by ordering, filtering and leveraging the problem structure

[04/04/2025] Games and Minimax Search

[11/04/2025] Alpha-Beta Pruning

[14/04/2025] Expectimax and state value evaluation functions

[05/05/2025] Montecarlo Tree Search and Introduction of Markov Decision Processes

[09/05/2025] Value iteration and policy evaluation

[12/05/2025] Policy iteration; Introduction of (passive) Reinforcement Learning, model-based approaches, direct (Monte Carlo) evaluation and Temporal Difference Learning

[16/05/2025] Q-learning; Exploration methods; Linear value functions; Policy search

[19/05/2025] Propositional logic

[23/05/2025] Inference in Propositional logic

[26/05/2025] DPLL; First-order Logic