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Major Topics Covered

Algorithms and representations for artificial intelligence

Search
Uninformed search
Informed search
Constraint Satisfaction*

Game Playing
Minimax
alpha-beta search
Introduction to game theory*


Reasoning under uncertainty
Probability
Bayes nets
Hidden Markov models and tracking

Planning
Decision theory
Stochastic planning (MDPs)
Reinforcement learning
Classical planning*

Introduction to machine learning
Classification
Introduction to neural networks and deep learning+

Logic and Knowledge Representation*
Propositional logic*
First order logic*
Theorem Proving*
Topics with a * will be given lower priority and will be covered towards the end of the semester, if at all. We will be attempting to give topics with a + greater emphasis this year.
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