Recurrent policy gradients

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چکیده

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Recurrent policy gradients

Reinforcement learning for partially observable Markov decision problems (POMDPs) is a challenge as it requires policies with an internal state. Traditional approaches suffer significantly from this shortcoming and usually make strong assumptions on the problem domain such as perfect system models, state-estimators and a Markovian hidden system. Recurrent neural networks (RNNs) offer a natural ...

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ژورنال

عنوان ژورنال: Logic Journal of IGPL

سال: 2009

ISSN: 1367-0751,1368-9894

DOI: 10.1093/jigpal/jzp049