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Reinforcement learning is generally perceived as a machine learning discipline in which an agent learns by interacting with its environment. What makes reinforcement learning unique is that it attempts to solve the credit assignment problem, in which an agent attempts to predict the long-term impact of its actions. Recent work seems to suggest that reinforcement learning, as a general formalism, does correspond to observable mammal brain functionality. In particular, the notion of a value function and of actions that are driven by such a value function has found proof in recent neurophysiological studies. However, despite almost two decades of RL research, there has been little solid evidence of RL systems that may one day lead to Artificial General Intelligence (AGI).
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