CS47100: Introduction to Artificial Intelligence (Spring 2024)

Images generated from DALL-E-2 with text prompt A class on Artificial Intelligence, digital art.


Course Information

Artificial intelligence (AI) is about building intelligent machines that can perceive and act rationally to achieve their goals. To prepare students for this endeavor, we cover the following topics in this course: Search, constraint satisfaction, logic, reasoning under uncertainty, machine learning, and planning. There will be four assignments in the form of both written and programming problems.

Pre-requisites:

Textbook:

Grading:

FAQ:

Instructor & TAs

Brian Bullins

Instructor

Email: bbullins [at] purdue.edu
Office Hour: Mon. 2PM-3PM
Location: Zoom (See Ed.)

Jiaxin Du

Teaching Assistant

Email: du286 [at] purdue.edu
Office Hour: Thurs. 2PM-3PM
Location: HAAS 143

Jinzhao Li

Teaching Assistant

Email: li4255 [at] purdue.edu
Office Hour: Fri. 3PM-4PM
Location: HAAS 143

Abhijeet Vyas

Teaching Assistant

Email: vyas26 [at] purdue.edu
Office Hour: Thurs. 5:30PM-6:30PM
Location: HAAS 143

Chiao An Yang

Teaching Assistant

Email: yang2300 [at] purdue.edu
Office Hour: Fri. 9AM-10AM
Location: HAAS G072

Hairong Yin

Teaching Assistant

Email: yin178 [at] purdue.edu
Office Hour: Tues. 1PM-2PM
Location: HAAS 143

Haomeng Zhang

Teaching Assistant

Email: zhan5050 [at] purdue.edu
Office Hour: Fri. 10AM-11AM
Location: HAAS 143

Time & Location

  • Time: Monday & Wednesday (6:00 pm - 7:15 pm)
  • Location: Forney Hall of Chemical Engineering (FRNY) G140

Other Resource

Course Schedule

The following schedule is tentative and subject to change.

DateEventDescriptionReadings
Jan 8 Lecture 1 Introduction & Overview

AIMA Ch. 1
Jan 10 Lecture 2 AI Representation

AIMA Ch. 2
Jan 15 --- Martin Luther King Jr. Day (No Classes)

Select from the following:
Jan 17 Lecture 3 Search - I: Problem Formulation

AIMA Ch. 3.1-3.3
Jan 22 Info. Assignment 1 released

Select from the following:
Jan 22 Lecture 4 Search - II: Uninformed Search

AIMA Ch. 3.4
Jan 24 Lecture 5 Search - III: Informed Search

AIMA Ch. 3.5-3.6
Jan 29 Lecture 6 Local search

AIMA Ch. 4.1
Jan 31 Lecture 7 Adversarial search - I: Minimax

AIMA Ch. 5.1-5.2
Feb 5 Lecture 8 Adversarial search - II: Alpha-Beta Pruning

AIMA Ch. 5.3-5.5
Feb 7 Lecture 9 CSP - I: Problem Formulation and Inference

AIMA Ch. 6.1-6.2
Feb 9 Deadline Assignment 1 due (Friday Feb 9, 11:59PM)

Select from the following:
Feb 12 Info. Assignment 2 released

Select from the following:
Feb 12 Lecture 10 CSP - II: Backtracking and Local Search

AIMA Ch. 6.3-6.5
Feb 14 Lecture 11 Logic - I: Propositional Logic

AIMA Ch. 7.2-7.4
Feb 19 Lecture 12 Logic - II: Propositional Theorem Proving

AIMA Ch. 7.5-7.6
Feb 21 Lecture 13 Logic - III: First Order Logic Semantics

AIMA Ch. 8.2-8.3
Feb 26 Lecture 14 Logic - IV: First Order Logic Inference

AIMA Ch. 9.1-9.5
Feb 28 Lecture 15 Probability and Uncertainty

AIMA Ch. 12.2-12.6
Mar 1 Deadline Assignment 2 due (Friday Mar 1, 11:59PM)

Select from the following:
Mar 4 Lecture 16 Midterm Review

Mar 6 --- No class (Evening midterm exam)

Select from the following:
Mar 7 Exam Evening midterm exam (8:00PM - 10:00PM)

Select from the following:
Mar 11 --- Spring Break

Select from the following:
Mar 13 --- Spring Break

Select from the following:
Mar 18 Info. Assignment 3 released

Select from the following:
Mar 18 Lecture 17 Bayesian Networks - I: Representation and Semantics

AIMA Ch. 13.1-13.2
Mar 20 Lecture 18 Bayesian Networks - II: Independence

Mar 25 Lecture 19 Bayesian Networks - III: Inference

AIMA Ch. 13.3-13.4
Mar 27 Lecture 20 Markov Decision Process - I: Problem Formulation

AIMA Ch. 17.1
Apr 1 Lecture 21 Markov Decision Process - II: Value Iteration

AIMA Ch. 17.2.1
Apr 3 Lecture 22 Markov Decision Process - III: Policy Iteration

AIMA Ch. 17.2.2
Apr 5 Deadline Assignment 3 due (Friday Apr 5, 11:59PM)

Select from the following:
Apr 8 Info. Assignment 4 released

Select from the following:
Apr 8 Lecture 23 Reinforcement Learning - I: Problem Formulation

AIMA Ch. 22.1-22.2
Apr 10 Lecture 24 Reinforcement Learning - II: Q-Learning

AIMA Ch. 22.3-22.4.2
Apr 15 Lecture 25 Supervised Learning - I: Overview

AIMA Ch. 19.1-19.2
Apr 17 Lecture 26 Supervised Learning - II: Model Search and Evaluation

AIMA Ch. 19.4
Apr 19 Deadline Assignment 4 due (Friday Apr 19, 11:59PM)

Select from the following:
Apr 22 Lecture 27 Supervised Learning - III: Deep Learning

Apr 24 Lecture 28 Final Review

May 1 Exam Final Exam (7:00PM - 9:00PM)

Select from the following:

Policies

Late & Absence Policy

A 10% penalty will be applied (per day) to late assignments. Assignments that are more than two days late will not be accepted. For the consistency and fairness to all students, we follow the policy and absence request through the Office of the Dean of Students.

Academic Honesty

Please refer to Purdue's Student Guide for Academic Integrity and the departmental academic integrity policy. Interaction among students is encouraged, and you should feel free to discuss the course with one another. However, unless otherwise noted, the work that you turn in should reflect your own efforts and knowledge. Academic dishonesty will result in an automatic zero on an assignment and your course grade will be reduced by one full letter grade. A second attempt will result in a failing grade for the course. It is one's responsibility to prevent others from copying your work.

Accessibility

Purdue University strives to make learning experiences as accessible as possible. If you anticipate or experience physical or academic barriers based on disability, please contact the Disability Resource Center at: drc@purdue.edu or by phone at 765-494-1247 and the course instructor to arrange for accommodations. If you have a DRC accommodation, please schedule your exams with Purdue Testing Services, and email the instructor if you have any questions.

Classroom Guidance Regarding Protect Purdue

Any student who has substantial reason to believe that another person is threatening the safety of others by not complying with Protect Purdue protocols is encouraged to report the behavior to and discuss the next steps with their instructor. Students also have the option of reporting the behavior to the Office of the Student Rights and Responsibilities. See also Purdue University Bill of Student Rights and the Violent Behavior Policy under University Resources in Brightspace.

University Policies

Please refer to additional university policies in Brightspace.