Aims
This module introduces basic principles of sequential decision making under uncertainty and the application in Reinforcement Learning and Control. Foundations and recent algorithms are covered.
Objectives:
On completion of this module, students should understand:
- the foundations of sequential decision making and reinforcement learning
- the connections between control and reinforcement learning
- the exploration vs exploitation trade-off.