Introduction to Artificial Intelligence
- introduction to AI
- problem-solving using state-space search
- uninformed search algorithms
- informed/heuristic search
- local search and optimization
- constraint satisfaction problems
- adversarial search and game-playing
- propositional logic
- first-order logic
- inference for first-order logic
- knowledge and uncertainty
- Bayesian networks
- Introduction to machine learning
- Machine learning: part 2
ARTIFICIAL INTELLIGENCE PPT
INSTRUCTOR: Geiger, Davi
Books: Artificial Intelligence: A Modern Approach. (Second Edition) by Stuart Russell and Peter Norvig
1. Introduction to Artificial Intelligence.
Intelligent Agents (ppt)
2. Problem Solving: Search, Informed Search, Game Playing
3.Computer Vision and Inference
Introduction to Computer Vision and Inference (ppt)
4. Knowledge and Logic
Propositional or Boolean Logic (ppt)
The extra class is this Friday, April 11th, at 3 pm (*not 5 pm*) in room 109, WWH. We will complete the inference in first order logic.
5. Uncertainty & Learning
Uncertainty and Probability (ppt)
Evaluation: 60% final exam, 40% mid term exam. Hoemworks are provided to help students learn the material, but no grading will be done.
Midterm Exam: Tuesday March 11th.
Final Exam: May 13th, 7pm to 9 pm
It covers all the material in the course, including chapter 18th, but not chapter 20th.
Last year, 2007, exam and solution is here (pdf)
Homeworks: Students are encouraged to work with others. There is no grading. Solutions will be posted two weeks after the problems are posted.
Posted January 30th.