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CPS 824

Reinforcement Learning

This course focuses on topics related to reinforcement learning. The course will cover making decisions under uncertainty, Markov decision processes, dynamic programming, temporal-difference learning, eligibility traces, value function approximation methods, Monte Carlo reinforcement learning methods, and the integration of learning and planning.
Weekly Contact: Lecture:3 hrs.
GPA Weight: 1.00
Course Count: 1.00
Billing Units: 1

Prerequisites

CPS 305 and CPS 420

Antirequisites

None

Co-Requisites

None

Custom Requisites

None

Mentioned in the Following Calendar Pages

*List may not include courses that are on a common table shared between programs.

Computer Science