学习笔记 | UCL Course on RL
Lecture 1
Video: https://www.youtube.com/watch?v=2pWv7GOvuf0
Slide: Introduction to Reinforcement Learning
Key points:
1. An RL agent may include one or more of these components:
- Policy: agent’s behaviour function
- Value function: how good is each state and/or action
- Model: agent’s representation of the environment
2. Two fundamental problems in sequential decision making
- Reinforcement Learning
- environment is unknown
- the agent interacts with the environment
- the agent improves its policy
- Planning
- environment is known
- the agent performs computations with its model
- the agent improves its policy
- aka diliberation, reasoning, introspection, pondering, thought
Jan 17, 2017
