Unsupervised Basis Function Adaptation for Reinforcement Learning

23 Mar 2017 Edward Barker Charl Ras

When using reinforcement learning (RL) algorithms it is common, given a large state space, to introduce some form of approximation architecture for the value function (VF). The exact form of this architecture can have a significant effect on an agent's performance, however, and determining a suitable approximation architecture can often be a highly complex task... (read more)

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