CS47100: Introduction to Artificial Intelligence (Fall 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 and one essay.

Pre-requisites:

Textbook:

Grading:

FAQ:

Instructor & TAs

Yexiang Xue

 Instructor

Email: yexiang [at] purdue.edu
Office Hour: Mon. 3:30PM-4:30PM
Location: Zoom, email 24 hours before

Jinzhao Li

Teaching Assistant

Email: li4255 [at] purdue.edu
Office Hour: 9-10 am on Tuesdays
Location: Zoom

Jiaxin Du

Teaching Assistant

Email: du286 [at] purdue.edu
Office Hour: 3-4 pm on Tuesdays
Location: Zoom

Haomeng Zhang

Teaching Assistant

Email: zhan5050 [at] purdue.edu
Office Hour: 2-3 pm on Wednesdays
Location: DSAI B061

Hairong Yin

Teaching Assistant

Email: yin178 [at] purdue.edu
Office Hour: 1-2 pm on Thursdays
Location: Zoom

Kai Cheng

Teaching Assistant

Email: cheng753 [at] purdue.edu
Office Hour: 2-3 pm on Fridays
Location: DSAI B061

Mutian Zhang

Teaching Assistant

Email: zhan5048 [at] purdue.edu
Office Hour: 9-10 am on Fridays
Location: DSAI B055

Medha Parhy

Undergraduate TA

Email: mparhy [at] purdue.edu
Office Hour: 3-4 pm on Fridays
Location: DSAI B055

Chirag Kaushik

Undergraduate TA

Email: kaushikc [at] purdue.edu
Office Hour: 3-4 pm on Thursdays
Location: Zoom

Time & Location

  • Time: Monday, Wednesday, and Friday (10:30 am - 11:20 am)
  • Location: FRNY G-140

Other Resource

Course Schedule

The following schedule is tentative and subject to change.

DateEventDescriptionReadings
Aug 19 Lecture 1 Introduction & Overview

AIMA Ch. 1
Aug 21 Lecture 2 AI Representation

AIMA Ch. 2
Aug 23 Lecture 3 AI Impact on Future Workforce

AIMA Ch. 2
Aug 26 Lecture 4 Search - I: Problem Formulation

AIMA Ch. 3.1-3.3
Aug 28 Lecture 5 Search - II: Uninformed Search

AIMA Ch. 3.4
Aug 30 Lecture 6 Search - III: Uninformed Search

AIMA Ch. 3.4
Sep 2 Info Labor Day Holiday, no lecture

Select from the following:
Sep 4 Lecture 7 Search - IV: Informed search

AIMA Ch. 3.5-3.6
Sep 6 Lecture 8 Local search

AIMA Ch. 4.1
Sep 9 Lecture 9 Adversarial search - I: Minimax

AIMA Ch. 5.1-5.2
Sep 11 Lecture 10 Adversarial search - II: Alpha-Beta Pruning

AIMA Ch. 5.3
Sep 13 Lecture 11 Adversarial search - III: Alpha-Beta Pruning

AIMA Ch. 5.3
Sep 16 Lecture 12 CSP - I: Problem Formulation and Inference

AIMA Ch. 6.1-6.2
Sep 18 Lecture 13 CSP - II: Problem Formulation and Inference

AIMA Ch. 6.1-6.2
Sep 20 Info Homework 1 Due at 10:30 am

Select from the following:
 AIMA Ch. 6.3-6.5
Sep 20 Lecture 14 CSP - III: Backtracking and Local Search

AIMA Ch. 6.3-6.5
Sep 23 Lecture 15 Logic - I: Propositional Logic

AIMA Ch. 7.2-7.4
Sep 25 Lecture 16 Logic - II: Propositional Logic

AIMA Ch. 7.2-7.4
Sep 27 Lecture 17 Logic - III: Propositional Theorem Proving

AIMA Ch. 7.5-7.6
Sep 30 Lecture 18 Logic - IV: First Order Logic Senmatics

AIMA Ch. 8.2-8.3
Oct 2 Lecture 19 Logic - V: First Order Logic Senmatics

AIMA Ch. 8.2-8.3
Oct 4 Lecture 20 Midterm Review

Oct 7 Info. October Break; No Lecture

Select from the following:
Oct 9 --- No class (making up for evening midterm exam)

Select from the following:
Oct 10 Exam Midterm: 8:00 -- 10:00 pm in BHEE 129

Select from the following:
Oct 11 --- No class (making up for evening midterm exam)

Select from the following:
Oct 14 Lecture 21 Probability and Uncertainty I

AIMA Ch. 12.2-12.6
Oct 16 Lecture 22 Probability and Uncertainty II

AIMA Ch. 12.2-12.6
Oct 18 Lecture 23 Probability Distributions

Oct 21 Lecture 24 Conditional Probabilities

Oct 23 Lecture 25 Bayesian Networks - I: Representation and Semantics

AIMA Ch. 13.1-13.2
Oct 25 Lecture 26 Bayesian Networks - II: Representation and Semantics

AIMA Ch. 13.1-13.2
Oct 28 Lecture 27 Bayesian Networks - II: Independence

Oct 30 Lecture 28 Bayesian Networks - III: Inference

AIMA Ch. 13.3-13.4
Nov 1 Lecture 29 Bayesian Networks - IV: Inference

AIMA Ch. 13.3-13.4
Nov 4 Lecture 30 Markov Decision Process - I: Problem Formulation

AIMA Ch. 17.1
Nov 6 Lecture 31 Markov Decision Process - II: Problem Formulation

AIMA Ch. 17.1
Nov 8 Lecture 32 Markov Decision Process - III: Value Iteration

AIMA Ch. 17.2.1
Nov 11 Lecture 33 Markov Decision Process - IV: Policy Iteration

AIMA Ch. 17.2.2
Nov 13 Lecture 34 Reinforcement Learning - I: Problem Formulation

AIMA Ch. 22.1-22.2
Nov 15 Lecture 35 Reinforcement Learning - II: Q-Learning

AIMA Ch. 22.3
Nov 18 Lecture 36 Supervised Learning - I: Overview

AIMA Ch. 19.1-19.2
Nov 20 Lecture 37 Supervised Learning - II: Methods

AIMA Ch. 19.1-19.2
Nov 22 Info. Supervised Learning - III: Model Search and Evaluation

Select from the following:
Nov 25 Lecture 38 Supervised Learning - IV: Cross Validation

AIMA Ch. 19.4
Nov 27 Info. Thanksgiving Break; No Lecture

Select from the following:
Nov 29 Info. Thanksgiving Break; No Lecture

Select from the following:
Dec 2 Lecture 39 Advanced AI Topics

AIMA Ch. 25
Dec 4 Lecture 40 Advanced AI Topics

Dec 6 Lecture 41 Final Review

Dec 12, 8:00 am -- 10:00 am Exam Final Exam (BHEE 129)

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. 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.

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.