CS 4700: Foundations of Artificial Intelligence

Fall 2014

Announcements

• Exam: Wedn., 12/17/13, 2pm-4:30pm, Baker Laboratory 200. See notes.

• Hwk. #4 has been posted. See below. Due: Wedn. Dec. 10, 11:59pm on CMS.

• Hwk. #3 has been posted. See below. Due: Tuesday Nov. 25, 5pm on CMS.

• Midterm: Thursday Oct. 23, 7:30pm, Kimball B11. (http://registrar.sas.cornell.edu/Sched/PRELF.html)

• Midterm: (1) Covers up to and including slide set #10 below (Adversarial Search), (2) Study slides and relevant Russell & Norvig parts, (3) look over Hwk #1 with solns, and (4) I released a short Hwk #2, with 3 questions to help you study/practice for the remaining materials.

• Hwk. #2 has been posted. See below. Due: Wedn., Oct 22, 10am, CMS. NOTE: no extensions because soln. will be released later that day to study for midterm.

• Hwk. #1 has been posted. See below. Due: Friday, Sept. 26, 10am, CMS.

Office hours: TBA

Personnel

Prof. Bart Selman <selman@cs.cornell.edu>

Ph.D. TAs:

Dylan Foster <djf244@cornell.edu>
Vasily Kuksenkov <vdk23@cornell.edu>
Andreas Veit <av443@cornell.edu>

MEng. TA:

Sneha Prasad Hebbur Narasimha Prasad <sh824@cornell.edu>

Undergraduate TAs:

Abdulkareem Adesokan <aaa257@cornell.edu>

Jonathan Hayon <joffin32@gmail.com>

Humale Khan <hak59@cornell.edu>

William Lee <wjl57@cornell.edu>

Siddharth Panchanathan <skp48@cornell.edu>

Michael Wang <mzw4@cornell.edu>

Jerry Yeh <jcy47@cornell.edu>

Peaky (Alex) Yuter <ajy34@cornell.edu>

Lecture Slides

1. Introduction (part 1) (pdf)

2. Introduction, cont. (part 2) (pdf)

   news link: When Machines Outsmart Humans

3. Agents (pdf)

4. Search --- Uninformed (pdf)

5. Search --- Informed (pdf)

6. Search --- Local Search (pdf)

7. Reinforcement Learning (RL) --- Intro (pdf)

8. RL --- Passive

9. RL --- Active

10. Adversarial search (pdf)

11. Adversarial search --- Games / Deep Blue (auxiliary materials) (pdf)

12. Knowledge Representation and Reasoning (KR&R) --- Part I (pdf)

13. KR&R --- Part II (pdf))

14. Machine Learning --- Intro (pdf))

15. Decision Tree Learning (pdf))

16. Neural Networks (pdf))

Homeworks

• Hwk. #1 (questions from book scanned pdf)

• Hwk. #2

• Hwk. #3

• Hwk. #4