Reinforcement Learning Algorithms with Python

Comparing RL and supervised learning

RL and supervised learning are similar, yet different, paradigms to learn from data. Many problems can be tackled with both supervised learning and RL; however, in most cases, they are suited to solve different tasks.

Supervised learning learns to generalize from a fixed dataset with a limited amount of data consisting of examples. Each example is composed of the input and the desired output (or label) that provides immediate learning feedback.

In comparison, RL is more focused on sequential actions that you can take in a particular situation. In this case, the only supervision provided is the reward signal. There's no correct action to take in a circumstance, as in the supervised settings.

RL can be viewed ...