Artificial Intelligence

No other field in computer science has greater visibility (and expectations, occasional disappointments, and remarkable achievements)
than artificial intelligence to the general population. This course covers the basic components of artificial intelligence, including search, optimization,
and machine learning. By the end of the semester, you should be able to build simple but interesting AI systems.

Administrative Details

Here you will find administrative information for the Winter 1403 semester.

• Instructor: Dr. Mohsen Afsharchi, afsharchim@znu.ac.ir
• Lectures: Sat 8-9:30, Tue 8-9:30
• Office Hours: Sat 10-12
• Prerequisites: Clear understanding of common data structures, algorithms, and standard programming.

Textbook

The required textbook for this course is:

• Artificial Intelligence: A Modern Approach (Fourth Edition), by Stuart J. Russell and Peter Norvig, Prentice Hall, 2020.

A supplementary textbook (recommended but not required) is:

• Artificial Intelligence: A New Synthesis , by Nils J. Nilsson, Morgan Kaufmann, 1999.

Lecture material will be drawn from both textbooks, as well as recent online AI literature.

Course Syllabus and Lecture Notes

• Introduction: AI history, state-of-the-art, CAPTCHA, ESP game. PDF
• Uninformed Search: DFS, BFS, iterative deepening. PDF
• Informed Search: BFS, Uniform-Cost search, Heuristic and A* search. PDF1, PDF2
• Constraint Satisfaction Problems (CSP): Backtracking, Forward Checking, Constraint Propagation. PDF
• Beyond Classical Search: Hill Climbing, Simulated Annealing, Genetic Algorithms. PDF, PDF
• Games: Adversarial Search, Minimax, Alpha-Beta Pruning. PDF
• Introduction to Machine Learning: Basic concepts. PDF
• k-Nearest-Neighbor Algorithm: PDF
• Decision Trees: Information gain, Overfitting. PDF, PDF
• Neural Networks: Perceptron, Multi-Layer Perceptrons, Convolutional Networks. PDF, PDF, PDF, PDF
• Markov Processes: Markov Models, Hidden Markov Models. PDF
• Markov Models: Applications: PDF
• Markov Decision Process: PDF
• Reinforcement Learning: PDF

Course Work and Evaluation

Possibly Interesting URLs

Here is an ad hoc collection of relevant AI links and interesting tidbits. If you know of other good resources, please share them.