CS 687

Advanced Aritificial IntelligenceTime/Location: Monday 7:20-10pm, Innovation Hall 204

Instructor: Jana Kosecka

Office hours: Wednesday 2-3pm

Contact: Office 4444 Research II, e-mail: kosecka@gmu.edu, 3-1876

Course web page: http://www.cs.gmu.edu/~kosecka/cs687/

Required Textbook:

[1] Russel and Norvig: Artificial Intelligence: A Modern Approach, 3rd edition

[2] Sutton and Barto: Reinforcement Learning: An Introduction

Some materials in this course are adopted from CS188 AI Course

Announcements

Piazza

Schedule (subject to change)

Mar 7th)

DateTopic, HandoutsAssignments/Due datesResourcesJan 24 Introduction and course logistics slides.pdf

Machine Learning slides.pdf

Linear Algebra Review slides.pdf

Getting started Project 0 (due Friday Feb 1st)

Chapter 18.6.3 Jan 31 Machine Learning, Neural Networks slides.pdf Project 1 (due Thursday Feb 21st)

Chapter 18.6-18.8

logistic regression notesFeb 7 Machine Learning, SVMs, Ensebmle Methods slides.pdf

Instance Based Methods, Approx. NN methods slides.pdf

svm guide Feb 14 Probabilistic Reasoning, Bayesian Networks slides.pdf Feb 21 Naive Bayes slides.pdf

Bayes Nets Independence slides.pdfHomework 1 (due Feb. 28) Feb 28 Bayes Nets Inference, Enumeration, Variable Elimination, Sampling slides.pdf

March 7 Temporal Models, HMM's, Kalman Filters, Particle filters slides.pdf

March 14 Spring Break

March 21 Temporal Models Cont, Kalman Filters, Particle filters

Homework 3 (due Mar 28th) March 28 Markov Decision Processes slides.pdf

April 4 Reinforcement Learning slides.pdf

April 11 Exam

April 19 Advanced Topics slides.pdf

April 11 Special Topics: Deep Learning, Natural Language Processing, Robotics, Vision

Project 2 (due May 2nd)