Publication Date
2008
Abstract
We describe the Fourier Basis, a linear value function approximation scheme based on the Fourier Series. We empirically evaluate its properties, and demonstrate that it performs well compared to Radial Basis Functions and the Polynomial Basis, the two most popular fixed bases for linear value function approximation, and is competitive with learned Proto-Value Functions even though no extra experience or computation is required.
Recommended Citation
Konidaris, George and Osentoski, Sarah, "Value Function Approximation in Reinforcement Learning using the Fourier Basis" (2008). Computer Science Department Faculty Publication Series. 101.
Retrieved from https://scholarworks.umass.edu/cs_faculty_pubs/101
Comments
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