How it works: In reinforcement learning, the computer learns certain behaviors or algorithms based on feedback from the environment. This algorithm can be learnt once or it could keep adapting using continuous feedback. Reinforcement learning overcomes some disadvantages of supervised learning, but is more complex and computationally expensive.