CS 438 - AI
2024 - Fall
An introduction to the concepts of artificial intelligence.
Tentative schedule is provided below – assignments dates and lectures will be updated as the course progresses.
Table of contents
- INTRO
- UNIT 1: Search
- UNIT 2: Constraint Satisfaction Problems & Adversarial Search
- UNIT 3: Markov Decision Processes and Reinforcement Learning
- UNIT 4: Probability, Bayesian Networks, and HMMs
- FINAL EXAM
INTRO
UNIT 1: Search
UNIT 2: Constraint Satisfaction Problems & Adversarial Search
UNIT 3: Markov Decision Processes and Reinforcement Learning
| WEEK 9 |
| UNIT 2 EXAM Wed. 10/16 |
| Markov Decision Processes I Videos: Lec 8 |
| Markov Decision Processes II Videos: Lec 9 |
| Notes - Markov Decision Process |
| Worksheet 4 - MDPsWorksheet 4 - Solution |
| P3 - Reinforcement Learning(Due: Fri. 11/15)HW3 - RL(Due: Fri. 11/15) |
| WEEK 10 |
| Reinforcement Learning I Videos: Lec 10 |
| Reinforcement Learning II Videos: Lec 11 |
| Notes - Reinforcement Learning |
| Worksheet 5 - RLWorksheet 5 - Solution |
| WEEK 11 |
| Exam Prep - MDPsExam Prep - MDP SOLN |
| Exam Prep - RLExam Prep - RL SOLN |
| WEEK 12 |
| Review Questions - MDPReview Questions - MDP SOLN |
| Review Questions - RLReview Questions - RL SOLN |
UNIT 4: Probability, Bayesian Networks, and HMMs
FINAL EXAM
| WEEK 17 |
| UNIT 4 EXAM Thur. 10:00 am - 11:40 am 12/12, EB 0165 |