CS 479: Introduction to Intelligent Agents using Science Fiction

Fall 2014

Class Information

Time: Tuesdays & Thursdays 1:10-2:25pm
Location: SH 113

Instructor

William Yeoh
Office: SH 173
Email: wyeoh@cs.nmsu.edu
Phone: (575) 646-5666
Office Hours: Tuesdays & Thursdays 3:00-4:00pm and by appointment

Schedule

Overview

  • Aug 21: Discussion of Syllabus and Class Rules [pdf]

BDI and Decision Theory

  • Aug 26: Belief-Desire-Intention Model [pdf]
  • Aug 28: Linear Programming [pdf]
  • Sep 2: Review of Probabilities [pdf]
  • Sep 4: Utility Theory [pdf]
  • Sep 9: Minority Report + Homework 1 out [pdf]
  • Sep 11: Minority Report
  • Sep 16: Markov Decision Processes [pdf (bw), pdf [color]] + Homework 1 due
  • Sep 18: Review for Midterm 1
  • Sep 23: Midterm 1

Game Theory

  • Sep 25: The Dark Knight
  • Sep 30: The Dark Knight
  • Oct 2: Classical Game Theory [pdf]
  • Oct 7: Classical Game Theory [pdf]
  • Oct 9: Classical Game Theory [pdf]
  • Oct 14: Classical Game Theory [pdf]
  • Oct 16: Auctions [pdf]
  • Oct 21: Auctions [pdf] + Homework 2 out [pdf]

Distributed Optimization

  • Oct 23: Ant Algorithms [pdf]
  • Oct 28: Edge of Tomorrow + Homework 2 due
  • Oct 30: Edge of Tomorrow
  • Nov 4: Distributed Constraint Satisfaction [pdf]
  • Nov 6: Review for Midterm 2
  • Nov 11: Midterm 2

Safety, Ethics, and Future of Agents

  • Nov 13: 2001 Space Odyssey + Homework 3 out [pdf]
  • Nov 18: 2001 Space Odyssey
  • Nov 20: I, Robot + Homework 4 out [pdf]
  • Nov 25: Thanksgiving Break
  • Nov 27: Thanksgiving Break
  • Dec 2: I, Robot + Homework 3 due
  • Dec 4: Class Wrap-up, Feedback, and Evaluations
  • Dec 9 (1-3pm): Homework 4 due

Syllabus

Instructor Information

William Yeoh
Office: SH 173
Email: wyeoh@cs.nmsu.edu
Phone: (575) 646-5666
Office Hours: Tuesdays & Thursdays 4:00-5:00pm and by appointment

Required Textbook

The course does not require any textbooks.

Course Overview

The course uses science-fiction literature (short stories, movies) to introduce fundamental principles and techniques in agents and multi-agent systems. It covers belief-desire-intention models, game theory, decision theory, and distributed optimization systems.

Learning Objectives

By the end of this course, you are expected to be able to

  • use decision-theoretic models and algorithms to represent and solve simple planning and reasoning problems under uncertainty.
  • use game-theoretic models and algorithms to represent and solve simple game-theoretic problems.
  • use auction models and algorithms to represent and solve simple resource and task allocation problems.
  • use distributed constraint-based reasoning models to represent simple distributed resource and task allocation problems.
  • understand the tradeoffs between the different agent models.

Attendance and Class Participation

The class participation portion of the grade will reflect how actively the student participates in class. Participation consists of attempts to answer questions asked of the class, asking questions about the material being discussed, contributing to class discussions and taking part in classroom activities.

Students are responsible for all lecture material, handouts and announcements given during class. Too many absences will make it very difficult for the student to complete the assignments and participate in the classroom satisfactorily.

Evaluation

There will be two midterm exams. The midterm exams will be on September 23 and November 11. There will be no make-up exams unless there is a very good documented reason to have it.

Homeworks: 40 %
Midterm Exams: 50%
Class Participation: 10%

Late submissions of projects and homeworks will not be accepted.

Grading Scale

The intended grading scale is as follows. The instructor reserves the right to adjust the grading scale.
A's (A-,A,A+): >= 90%
B's (B-,B,B+): >= 80%
C's (C-,C,C+): >= 70%
D's (D-,D,D+): >= 60%
F: < 60%

Incomplete ("I") Grades

An "I" grade may be given for possible work that could not be completed due to circumstances beyond the student's control (e.g., severe illness, death in the immediate family). These circumstances must have developed after the last day to withdraw from the course. Requests for "I" grades should be made to the instructor, but must be approved by the department chair. In no case will an "I" grade be assigned to avoid a grade of "D" or "F" in the course.

Withdrawals

It is the responsibility of the student to know important dates such as University drop dates. Moreover, it is the responsibility of the student to officially withdraw from any class he or she intends to drop.

Students with Disabilities

Section 504 of the Rehabilitation Act of 1973 and the Americans with Disabilities Act Amendments Act (ADAAA) covers issues relating to disability and accommodations. If a student has questions or needs an accommodation in the classroom (all medical information is treated confidentially), contact:

Trudy Luken
Student Accessibility Services (SAS) Corbett Center, Rm. 244
Phone: (585) 646-6840
E-mail: sas@nmsu.edu
Website: http://sas.nmsu.edu/

Do not wait until you receive a failing grade. Retroactive accommodations cannot be considered.

Academic Misconduct

Students should familiarize themselves with the NMSU Student Code of Conduct (found in the NMSU Student Handbook). Any violation of the Student Code of Conduct (e.g., plagiarism, cheating, etc.) will result in the student receiving a grade of "F" in this course. If you do not have a Student Handbook, this information is available here: http://deanofstudents.nmsu.edu/student-handbook.

Plagiarism is using another person's work without acknowledgment, making it appear to be one's own. Intentional and unintentional instances of plagiarism are considered instances of academic misconduct and are subject to disciplinary action such as failure on the assignment, failure of the course or dismissal from the university. The NMSU Library has more information and help on how to avoid plagiarism at http://lib.nmsu.edu/plagiarism.

Discrimination

NMSU policy prohibits discrimination on the basis of age, ancestry, color, disability, gender identity, genetic information, national origin, race, religion, retaliation, serious medical condition, sex, sexual orientation, spousal affiliation, and protected veterans status. Furthermore, Title IX prohibits sex discrimination to include sexual misconduct, sexual violence (sexual assault, rape), sexual harassment, and retaliation.

For more information on discrimination issues, Title IX or NMSU's complaint process contact:

Gerard Nevarez or Agustin Diaz
Office of Institutional Equity (OIE) O'Loughlin House
1130 University Avenue
Phone: (585) 646-3635
E-mail: equity@nmsu.edu
Website: http://www.nmsu.edu/∼eeo/

Academic Integrity Policy

Academic dishonesty includes (but not limited to) the following:

  • Giving or receiving information during an exam.
  • Unauthorized or malicious use of computing facilities.
  • Deception or misrepresentation in a student's dealing with the instructor, teaching assistant, or grader.
  • Inappropriate collaboration on or coping of homework assignments. Students are encouraged to discuss the readings with one another, even when the discussion relates to assignments. As long as the purpose of discussion is to help the student's understanding of the material, and not to reduce or share the work, such discussion will not be deemed inappropriate.
  • Plagiarism, the submission of material authored by another person but represented as the students own work. It does not matter whether the original work author gave permission.
  • Any violation of academic integrity standards described in the student conduct code. Students are expected to be familiar with these standards.

All students are responsible for reading and following the NMSU Student Code of Conduct (found in the NMSU Student Handbook). Any violation of the Student Code of Conduct will result in the student receiving a grade of "F" in this course. If you do not have a Student Handbook, this information is available here: http://deanofstudents.nmsu.edu/student-handbook.

Acknowledgement

The structure of this course follows a similar course taught by Milind Tambe at University of Southern California. We very much appreciate his help in sharing with us his materials, which we adapted for this course.