Pepe's Braindump

Reinforcement learning

Machine Learning

In reinforcement learning the model is in an environment of which it can see the state and perform its predictions. After performing them, it checks the optimality of them before moving to a new state.

The difference with supervised learning is that in RL, learning is sequential, one needs to adjust with every prediction in order to achieve good results.

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