Introduction to Artificial Intelligence

• Lecture 1: Introduction
• Lecture 2: Agents
• Lecture 3: Discrete Search Strategies
• Lecture 4: Heuristic Search Algorithms
• Lecture 5: Constrained Satisfaction Problems
• Lecture 6: Adversarial Games     Additional Note     Alpha-Beta Pruning Example
• Lecture 7: Propositional Logic    Intro to PROLOG
• Lecture 8: Satisfiability
• Lecture 9: Predicate Logic
• Lecture 10: Fuzzy Logic
• Lecture 11: Decisions and Utility
• Lecture 12a: Machine Learning (1)
• Lecture 12b: Machine Learning (2)

• Exercise 1 (Introduction)
• Exercise 2 (Search)
• Exercise 3 (Heuristics)
• Exercise 4 (Constrained Satisfaction)
• Exercise 5 (Adversarial Games)
• Exercise 6 (Propositional Logic)
• Exercise 7 (Predicate Logic)
• Exercise 8 (Fuzzy Logic)
• Exercise 9 (Utility Theory) Example Solution

• Skeleton Code for the Final Project (5-wins)