CS47100: Introduction to Artificial Intelligence (Spring 2023)
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:
- CS251 Data Structures (grade of C or better)
Textbook:
- [AIMA] S. Russell and P. Norvig (2020). Artificial Intelligence: A Modern Approach. Pearson, 4th Edition. (ISBN:9780134610993)
- You can also use the 3rd edition and find the corresponding sections to read.
Grading:
- Assignments: 40% (10% each)
- Midterm: 30%
- Final Exam: 30%
FAQ:
- Lecture slides and recordings will be posted on Brightspace.
- The instructor & TAs can be best reached through Ed Discussion. Please post your questions there instead of emailing TAs.
- During office hours or on Ed Discussion, please avoid posting partial homework solutions or asking TAs to "review" your code.
- Zoom links for office hours are posted on Ed Discussion.
- Tutorial for learning Latex with Overleaf: [Link]
Instructor & TAs
Raymond A. Yeh
Instructor
Email: rayyeh [at] purdue.edu
Office Hour: Mon 4-5PM
Location: Zoom
Jiaxin Du
Teaching Assistant
Email: du286 [at] purdue.edu
Office Hour: Thu 4-5PM
Location: Zoom
Jinzhao Li
Teaching Assistant
Email: li4255 [at] purdue.edu
Office Hour: Fri 10-11AM
Location: Zoom
Zhuoyan Li
Teaching Assistant
Email: li4178 [at] purdue.edu
Office Hour: Wed 10-11AM
Location: Zoom
Mir Imtiaz Mostafiz
Teaching Assistant
Email: mmostafi [at] purdue.edu
Office Hour: Fri 12PM-1PM
Location: Zoom
Xinru Wang
Teaching Assistant
Email: xinruw [at] purdue.edu
Office Hour: Tue 10:30-11:30AM
Location: Zoom
Ananya Singh
Undergraduate TA
Email: singh745 [at] purdue.edu
Office Hour: Mon 3-4PM
Location: Zoom
Time & Location
- Time: Mon. & Wed. (5:30 pm - 6:45 pm)
- Location: Lilly Hall of Life Sciences G126
Other Resource
Course Schedule
The following schedule is tentative and subject to change.
| Date | Event | Description | Readings |
|---|---|---|---|
| Jan. 9 | Lecture 1 | Introduction & Overview
|
AIMA Ch. 1 |
| Jan. 11 | Lecture 2 | AI Representation
|
AIMA Ch. 2 |
| Jan. 16 | --- | Martin Luther King Jr. Day (No Classes)
Select from the following: |
|
| Jan. 18 | Lecture 3 | Search - I: Problem Formulation
|
AIMA Ch. 3.1-3.3 |
| Jan 23 | Info. | Assignment 1 released
Select from the following: |
|
| Jan 23 | Lecture 4 | Search - II: Uninformed Search
|
AIMA Ch. 3.4 |
| Jan 25 | Lecture 5 | Search - III: Informed search
|
AIMA Ch. 3.5-3.6 |
| Jan 30 | Lecture 6 | Local search
|
AIMA Ch. 4.1 |
| Feb 1 | Lecture 7 | Adversarial search - I: Minimax
|
AIMA Ch. 5.1-5.2 |
| Feb 6 | Lecture 8 | Adversarial search - II: Alpha-Beta Pruning
|
AIMA Ch. 5.3 |
| Feb 8 | Lecture 9 | CSP - I: Problem Formulation and Inference
|
AIMA Ch. 6.1-6.2 |
| Feb 13 | Lecture 10 | CSP - II: Backtracking and Local Search
|
AIMA Ch. 6.3-6.5 |
| Feb 15 | Lecture 11 | Logic - I: Propositional Logic
|
AIMA Ch. 7.2-7.4 |
| Feb 17 | Deadline | Assignment 1 due (Friday 17, 11:59PM)
Select from the following: |
|
| Feb 20 | Info. | Assignment 2 released
Select from the following: |
|
| Feb 20 | Lecture 12 | Logic - II: Propositional Theorem Proving
|
AIMA Ch. 7.5-7.6 |
| Feb 22 | Lecture 13 | Logic - III: First Order Logic Senmatics
|
AIMA Ch. 8.2-8.3 |
| Feb 27 | Lecture 14 | Logic - IV: First Order Logic Inference
|
AIMA Ch. 9.1-9.5 |
| Mar 1 | Lecture 15 | Probability and Uncertainty
|
AIMA Ch. 12.2-12.6 |
| Mar 3 | Deadline | Assignment 2 due (Friday Mar 3, 11:59PM)
Select from the following: |
|
| Mar 6 | Lecture 16 | Midterm Review
|
|
| Mar 8 | --- | No class (Evening midterm exam)
Select from the following: |
|
| Mar 8 | Exam | Evening midterm exam (8:00PM - 10:00PM)
Select from the following: |
|
| Mar 13 | --- | Spring Break
Select from the following: |
|
| Mar 15 | --- | Spring Break
Select from the following: |
|
| Mar 20 | Info. | Assignment 3 released
Select from the following: |
|
| Mar 20 | Lecture 17 | Bayesian Networks - I: Representation and Semantics
|
AIMA Ch. 13.1-13.2 |
| Mar 22 | Lecture 18 | Bayesian Networks - II: Independence
|
|
| Mar 27 | Lecture 19 | Bayesian Networks - III: Inference
|
AIMA Ch. 13.3-13.4 |
| Mar 29 | Lecture 20 | Markov Decision Process - I: Problem Formulation
|
AIMA Ch. 17.1 |
| Apr 3 | Lecture 21 | Markov Decision Process - II: Value Iteration
|
AIMA Ch. 17.2.1 |
| Apr 5 | Lecture 22 | Markov Decision Process - III: Policy Iteration
|
AIMA Ch. 17.2.2 |
| Apr 7 | Deadline | Assignment 3 due (Friday Apr 7, 11:59PM)
Select from the following: |
|
| Apr 10 | Info. | Assignment 4 released
Select from the following: |
|
| Apr 10 | Lecture 23 | Reinforcement Learning - I: Problem Formulation
|
AIMA Ch. 22.1-22.2 |
| Apr 12 | Lecture 24 | Reinforcement Learning - II: Q-Learning
|
AIMA Ch. 22.3 |
| Apr 17 | Lecture 25 | Supervised Learning - I: Overview
|
AIMA Ch. 19.1-19.2 |
| Apr 19 | Lecture 26 | Supervised Learning - II: Model Search and Evaluation
|
AIMA Ch. 19.4 |
| Apr 23 | Deadline | Assignment 4 due (Sunday, Apr 23 11:59PM)
Select from the following: |
|
| Apr 24 | Lecture 27 | Computer Vision
|
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| Apr 26 | Lecture 28 | Final Review
|
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| May 1 | Exam | Final Exams (7:00PM to 9:00PM)
Select from the following: |