CPS 680 - Graduate Artificial Intelligence
CPS 680 prepares graduate students to search, knowledge representation, machine learning, neural networks, evolutionary and bio inspired computation techniques, intelligent agents, and expert systems.
Lecture Slides:
Week 1 - Introduction
Introductions
Lecture 2 - AI vs ML - Whiteboard Notes
Video: TicTacToe 1950s AI
Week 2 - Rationality
Lecture 3 - Turing Test - Whiteboard Notes
Lecture 4 - Rationality
Week 3 - Agents
Lecture 5 - Agents - Whiteboard Notes
Week 4 - Research Paper Intro
Lecture 6 - How to Write A Paper
Detailed Paper Writing Tips (from Eamonn Keogh)
Lecture 7 - How to Read A Paper
Week 5 - Search & Bayes Theorem
Lecture 11 - Reflex and Planning Agents
Lecture - Search
Week 6 - Search
Lecture 17 - Search
Week 7 - Search (Cont.)
Week 8 - Bayes Theorem & Exam Review
Lecture 18 - Dijstra’s Algorithm
Lecture 19 - Midterm Review & Study Guide Answers
Week 9 - No class (Spring Break)
Week 10 - Exam
Week 11 - Open AI Introduction
Week 12 - No class (CMU Gentle Break)
Week 13 - Open AI (Cont).
Week 14 - Exam II & Paper Review
[T] - T2 (9:30am) / T10 (9:45am) / T1 (10:00am) / T6 (10:15am) / T7 (10:30 am)
[Th] - T3 (9:30am) / T5 (9:45am) / T8 (10:00am) / T4 (10:15am) / T9 (10:30 am)
Week 15 - Review and Exam II
[T] - Review
[Th] - Exam II (April 28th)
Assignments:
Assignment 1 - Proposal (due Mar 24th)
Assignment 2 - Background (due Apr 5th)
Assignment 3 - Introduction (due Apr 9th)
Assignment 4 - Methods (due Apr 14th)
Assignment 5 - Results (due Apr 28th)
Assignment 6 - Abstract, Conclusions, and Term Paper Complete (May 3rd)
Handouts
Number of students: 30