Volunteers

Supervised

Algorithms

Un-supervised

Algorithms

Reinforcement Learning

1. Active Learning
2. No labeled data
3. Can afford to make mistakes?
4. Is it possible to use a simulated environment for the task?
5. Lots of time
6. Think about the variables that can define the state of the environment.
1. State Variables and Quantify them
2. The agent has access to these variables at every time step
3. Concrete Reward Function and Compute Reward after action
4. Define Policy Function

Algorithms