# Value-function Approximation

**Source**:: 2018 Reinforcement Learning An Introduction

- Extending Reinforcement Learning to
*function approximation*also makes it applicable to*partially observable problems*, in which the full state is not available to the agent.

# # Value-function Approximation

- Function approximation methods expect to receive examples of the desired inputâ€“output behavior of the function they are trying to approximate.
- Not all function approximation methods are equally well suited for use in reinforcement learning.
- Methods that are able to from online and nonstationary settings are preferable in Reinforcement Learning.