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Andrew Barto

Known as: Andrew G. Barto, Barto, Barto, Andrew G. 
Andrew Barto is a professor of computer science at University of Massachusetts Amherst, and chair of the department since January 2007. His main… Expand
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Papers overview

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Highly Cited
2018
Highly Cited
2018
The deep reinforcement learning community has made several independent improvements to the DQN algorithm. However, it is unclear… Expand
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Highly Cited
2016
Highly Cited
2016
The popular Q-learning algorithm is known to overestimate action values under certain conditions. It was not previously known… Expand
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Highly Cited
2005
Highly Cited
2005
Reinforcement learning, one of the most active research areas in artificial intelligence, is a computational approach to learning… Expand
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Highly Cited
2005
Highly Cited
2005
Temporal difference (TD) learning methods (Sutton & Barto 1998) have become popular reinforcement learning techniques in recent… Expand
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Highly Cited
2003
Highly Cited
2003
We consider policy evaluation algorithms within the context of infinite-horizon dynamic programming problems with discounted cost… Expand
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Highly Cited
2000
Highly Cited
2000
Decision making usually involves choosing among different courses of action over a broad range of time scales. For instance, a… Expand
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Highly Cited
2000
Highly Cited
2000
In this paper, we propose a hierarchical reinforcement learning architecture that realizes practical learning speed in real… Expand
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Highly Cited
1999
Highly Cited
1999
Learning, planning, and representing knowledge at multiple levels of temporal ab- straction are key, longstanding challenges for… Expand
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Highly Cited
1998
Highly Cited
1998
 
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Highly Cited
1990
Highly Cited
1990
This paper extends previous work with Dyna, a class of architectures for intelligent systems based on approximating dynamic… Expand
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