1
Introduction & Intelligent Agents
What AI is, the four approaches, rational agents, PEAS, environment types, and the agent architecture ladder.
← Courses · AI Study Material
Each module is provided as a PDF (opens in any browser, best on a phone) and as PowerPoint (PPTX) (editable, for offline use). The slides cover the full syllabus with worked examples and exam-focused notes. Free to download — no sign-up.
2
Problem Solving by Searching
Search trees, BFS, DFS, iterative deepening, uniform-cost search, heuristics, greedy best-first and A*, with worked examples on the Romania map.
3
Knowledge Representation & Reasoning
Knowledge-based agents, the Wumpus world, propositional logic, CNF and resolution, first-order logic, quantifiers, unification, forward and backward chaining.
4
Reinforcement Learning
MDPs and the Bellman equation, passive RL (direct utility estimation, ADP, temporal difference), active RL, exploration vs exploitation, Q-learning, function approximation and policy search.
Reference: Russell & Norvig, Artificial Intelligence: A Modern Approach. Slides are teaching aids and do not replace the textbook or the KTU syllabus.