Courses Detail Information

VE492 – Introduction to Artificial Intelligence


Instructor: Paul Weng

Instructors (Faculty):

Credits: 4 credits

Pre-requisites: Ve 281

Description:

This course offers an overview and introduction to Artificial Intelligence: building blocks of intelligent systems (search, reasoning under certainty and uncertainty, decision-making, learning), some key algorithms, and their applications.

Course Topics:

  1. Agents and environments
  2. Uninformed and informed Search
  3. Adversarial search and search under uncertainty
  4. Decision theory and game theory
  5. Markov decision process
  6. Reinforcement learning
  7. Constraint satisfaction problem
  8. Probability review
  9. Bayesian network
  10. Markov chain and hidden Markov models
  11. Generative approach in machine learning
  12. Discriminative approach in machine learning
  13. Neural networks
  14. Logical Agents
  15. Propositional logic
  16. First-order logic
  17. Classical planning