Fourier policy gradients

Fourier policy gradients

We propose a new way of deriving policy gradient updates for reinforcement learning. Our technique, based on Fourier analysis, recasts integrals that arise with expected policy gradients as convolutions and turns them into multiplications. The obtained analytical solutions allow us to capture the lo...

書誌詳細
主要な著者:	Fellows, M, Ciosek, K, Whiteson, S
フォーマット:	Conference item
出版事項:	Journal of Machine Learning Research 2018

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