What are the main features of reinforcement learning, in a nutshell?
Is reinforcement learning likely to be better in general than other ML techniques e.g. faster learning, more accurate results?
RL is a framework for decision-making in a dynamic environment. It is not a specific machine learning model like a neural network or support vector machine. RL often uses these machine learning models but is a framework, not a model. RL is useful for decision-making problems where you do not know the "right" answer (there are no labels), you just know how to quantify better and worse answers/decisions. If you speak abstract math, RL is like a mathematical structure like a group that may contain a function (being akin to a specific machine learning model.)
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