AI Spring ¡®22
Final Exam: Syllabus
Location: The final exam is in 60FA Room 150, 6pm May 11th.
Bring your student ID as I will be going around and checking these as per a department request.
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Type: It is a written exam, blue books and such, but it is
Open: notes, computer, internet, labs. E.g. you are welcome to use your lab2 to assist you if I ask a BNF->CNF and DPLL question.
However: it is Closed communication. You may not discuss the Lab with anyone other than the Professor. (You may not post questions online to stackoverflow, or any other site)
Any topic covered in the notes and/or covered in class through Lecture 13 is fair game.
If it is in the textbook but I did not cover it in class, then I will not ask you about it on the final. Whenever possible show your work as much as possible for partial credit. If you use code or a program, don¡¯t just copy the answer but describe what you did.
¡ñ State space search: blind, informed, local (hill climbing)
¡ñ Adversarial search: minimax + alpha beta
¡ñ CSP: Propositional logic, BNF->CNF, DPLL
¡ñ First Order Logic and Resolution Theroem Proving
¡ñ Probabilities: conjunctive rule, Bayes¡¯ Law
¡ñ Decision Theory and MDPs
¡ñ Supervised learning: kNN, gradient descent and linear models
¡ñ Unsupervised learning: clustering
¡ñ Model evaluation
¡ñ Information Theory and MDL
¡ñ Deep learning: Perceptron and activation functions, regularization
¡ñ Reinforcement learning
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