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Evaluative versus instructive feedback

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Building upon the elements highlighted in the previous steps, we can now delve deeper into the fundamental distinction between reinforcement learning and other learning paradigms. Their purpose is to prepare a framework for understanding the problem deeply, to develop solutions and to establish common terms to recurring elements of the challenge.

However, these details are not the essential distinction between reinforcement learning and other forms of learning. What is most important to appreciate is that reinforcement learning uses the interaction with the environment, i.e. its experience E, to evaluate actions. By evaluate we mean assessing how good or bad a particular action was for a specific situation. In contrast, with supervised learning, the feedback is instructive rather than evaluative. With instructive feedback, your agent is told what the correct (or labelled) action is. This is done independently of the action presented by the agent; the action is not evaluated, nor even considered. The labelled action for that training instance is simply presented as feedback. In summary, evaluative feedback is a direct function of the action and this is what occurs in reinforcement learning. This is in contrast to instructive feedback which is completely independent of the action and which occurs in supervised learning. With this distinction clarified, we will now explore real-world reinforcement learning problems to observe the concept in action and develop specific strategies.

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