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The recent adaptation of deep neural network-based methods to reinforcement learning and planning domains has yielded remarkable progress on individual tasks.
Cognitive psychology and its implications
Anderson, John R · 1990
Earlier work this paper cites.
Made-up minds: a constructivist approach to artificial intelligence
Drescher, Gary L · 1991
Earlier work this paper cites.
Learning in graphical models , volume 89
Jordan, Michael Irwin · 1998
Earlier work this paper cites.
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Attias, Hagai · 2003
Earlier work this paper cites.
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Diuk, Carlos, Cohen, Andre, and Littman, Michael L · 2008
Earlier work this paper cites.
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Earlier work this paper cites.
Transfer learning for reinforcement learning domains: A survey
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Earlier work this paper cites.
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Jaakkola, Tommi S, Sontag, David, Globerson, Amir, Meila, Marina, et al · 2010
Earlier work this paper cites.
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Cited alongside, same era.
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Later among the works it cites.
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Later among the works it cites.
Rusu, Andrei A, Rabinowitz, Neil C, Desjardins, Guillaume, Soyer, Hubert, Kirkpatrick, James, Kavukcuoglu, Koray, Pascanu, Razvan, and Hadsell, Raia · 2016
Later among the works it cites.
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Cited in the paper.
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Later among the works it cites.