Before we can find a model, we must forget about perfection

10 Dec 2019Dimiter Dobrev

With Reinforcement Learning we assume that a model of the world does exist. We assume furthermore that the model in question is perfect (i.e. it describes the world completely and unambiguously)... (read more)

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