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We present an approach to training neural networks to generate sequences using actor-critic methods from reinforcement learning (RL).
Neuronlike adaptive elements that can solve difficult learning control problems
Andrew G Barto, Richard S Sutton, and Charles W Anderson · 1983
Earlier work this paper cites.
Temporal credit assignment in reinforcement learning
Richard Stuart Sutton · 1984
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Learning to predict by the methods of temporal differences
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Simple statistical gradient-following algorithms for connectionist reinforcement learning
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John N Tsitsiklis and Benjamin Van Roy · 1997
Earlier work this paper cites.
Introduction to reinforcement learning , volume 135
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Earlier work this paper cites.
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Earlier work this paper cites.
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Earlier work this paper cites.
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