Sparse Value Function Approximation for Reinforcement Learning
<p>A key component of many reinforcement learning (RL) algorithms is the approximation of the value function. The design and selection of features for approximation in RL is crucial, and an ongoing area of research. One approach to the problem of feature selection is to apply sparsity-inducin...
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2013
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| Online Access: | http://hdl.handle.net/10161/7250 |