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Reinforcement Learning is not a Causal problem

Published 20 Aug 2019 in cs.AI and cs.LG | (1908.07617v2)

Abstract: We use an analogy between non-isomorphic mathematical structures defined over the same set and the algebras induced by associative and causal levels of information in order to argue that Reinforcement Learning, in its current formulation, is not a causal problem, independently if the motivation behind it has to do with an agent taking actions.

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