1. Big Ideas in Cmput366

2. Search Blind Search Iterative deepening Heuristic Search A* Local and Stochastic Search Randomized algorithm Constraint satisfaction Arc consistency Edge labeling example Games and Adversarial Search Minimax Alpha-Beta

3. Logic Propositional Logic Soundness and completeness of inference Resolution rule Predicate Logic Unification Planning STRIP language

4. Probability Uncertainty and Probability Bayes theorem Chain rule Formulating problems as probabilistic reasoning Bayesian Network Representation of independence/d-separation Markov Model Computing expected values HMM and Speech Recognition Viterbi algorithm Baum-Welch algorithm

5. NLP NLP Overview Pervasiveness of ambiguity Parse trees Syntax and parsing CFG grammar Chart parsing Statistical Machine Translation Word alignment A general idea of EM