Units:

12

Description:

This is a first-year graduate course in Principles and Engineering Applications of AI. The course will review the basic principles of AI. Some of the specific topics that will be covered are the following:

1) Intelligent Agents
2) Single-Agents and Multi-Agent Systems (MAS)
3) Uncertain Knowledge and Reasoning (Probabilistic Reasoning and Probabilistic Reasoning over Time, Bayesian Networks, Dynamic Bayesian Networks, Hidden Markov Models, Kalman Filters, MCMC algorithms, etc.)
4) Learning
5) Communicating, Perceiving, and Acting
6) Robotics

The course will involve completing a set of challenging engineering applications of AI that will include: Medical applications, Video Games, Autonomous driving, Autonomous Robots, Finance and Economics, Military, Art, Advertising. Students should have a good background in basic probability theory, maturity in mathematical topics, and good programming skills. For seniors who would like to take the course but do not have the necessary prerequisites, instructor's permission will be required. Although students in 18-462 will share lectures with students in 18-662, students in 18-462 will receive distinct homework assignments, distinct projects, and distinct exams from the ones given to students in 18-662. Specifically, the homework assignments, projects, and exams that are given to the 18-662 students will be more challenging than those given to the 18-462 students.

Prerequisites: 18-751 or 36219 or 36218 or 36217

Last Modified: 2024-01-19 11:11AM

Semesters offered:

• Spring 2024
• Spring 2023
• Spring 2022
• Spring 2021
• Spring 2020