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 update when the agent’s goals, or the state of the world, changes in some [...]