Deep Reinforcement Learning. (3-0) 3 Credit Hours

Catalog description

Prerequisite: CS 5233 and CS 6283 , or consent of instructor. This course covers the theory and the approaches to building autonomous agents that learn to act and accomplish goals in dynamic environments. Topics include Markov decision processes (MDPs), learning behavioral policies, police gradients, policy iteration, value iteration, agent explorations vs. exploitation, Q learning, and DNN for RL. This course has Differential Tuition. Course Fee: GA02 $90; IUCA $45.