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Daily Archives: 21 June, 2009
Reinforcement learning in the brain
Model-free reinforcement learning (RL) algorithms are computationally cheap as each state-action pair keeps a cached estimate of its value that can easily be looked up in order to make a decision. Their weakness is that they are not easy to … Continue reading