18-662 Principles and Engineering Applications of AI
Location: Pittsburgh
Units: 12
Semester Offered: Spring
Course description
The course will review the basic principles of AI. Some of the specific topics that will be covered are the following:
- Intelligent Agents
- Single-Agents and Multi-Agent Systems (MAS)
- Uncertain Knowledge and Reasoning (Probabilistic Reasoning and Probabilistic Reasoning over Time, Bayesian Networks, Dynamic Bayesian Networks, Hidden Markov Models, Kalman Filters, MCMC algorithms, etc.)
- Learning
- Communicating, Perceiving, and Acting
- 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, and advertising. Students should have a good background in basic probability theory, maturity in mathematical topics, and good programming skills. permission will be required.
See the original course description for the most recent information.
Prerequisites
18-751 Applied Stochastic Processes with a minimum grade of B.
For seniors who would like to take the course but do not have the necessary prerequisites, instructor’s