CSE 511A: Introduction to Artificial Intelligence – Fall 2017

Instructor: Professor Roman Garnett
TAs: Zimu Wang (zimu.want), Matthew Ranftle (matthew.ranftle)
Time/Location: Monday/Wednesday 4–5:30pm, Hillman Hall 70
Office hours (Garnett): TBA
Office hours (TAs): TBA
syllabus
Piazza message board Please ask all questions on Piazza!


Description

The discipline of artificial intelligence (AI) is concerned with building systems that think and act like humans or rationally on some absolute scale. This course is an introduction to the field, with special emphasis on sound modern methods. The topics include knowledge representation, problem solving via search, game playing, logical and probabilistic reasoning, planning, machine learning (decision trees, neural nets, reinforcement learning, and genetic algorithms) and machine vision. Programming exercises will concretize the key methods. The course targets graduate students and advanced undergraduates. Evaluation is based on programming assignments, a midterm exam, and a final exam.

Prerequisites

If you are unsure about any of these, please speak with the instructor.

Assignments

Please post all questions to Piazza!

You can find autograder information here.

Lectures

Resources

This course is based on the CS 188 course at UC Berkeley. You may find lectures, slides, and more there.

Books

The required book for this course is Artificial Intelligence: A Modern Approach by Stuart Russell and Peter Norvig. Either the second or third edition is fine. This is a classic textbook and highly recommended!

Another good reference for reinforcement learning is Reinforcement Learning: An Introduction by Richard S. Sutton and Andrew G. Barto. The book is available online here.

Python help