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As demand drives systems to generalize to various domains and problems, the study of multitask, transfer and lifelong learning has become an increasingly important pursuit.
Catastrophic interference in connectionist networks: The sequential learning problem
McCloskey, Michael and Cohen, Neal J · 1989
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Is learning the n-th thing any easier than learning the first?
Thrun, Sebastian · 1996
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Multitask learning
Caruana, Rich · 1998
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Online multi-task learning for policy gradient methods
Ammar, Haitham B, Eaton, Eric, Ruvolo, Paul, and Taylor, Matthew · 2014
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Actor-mimic: Deep multitask and transfer reinforcement learning
Parisotto, Emilio, Ba, Jimmy Lei, and Salakhutdinov, Ruslan · 2015
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Rusu, Andrei A, Colmenarejo, Sergio Gomez, Gulcehre, Caglar, Desjardins, Guillaume, Kirkpatrick, James, Pascanu, Razvan, Mnih, Volodymyr, Kavukcuoglu, Koray, and Hadsell, Raia · 2015
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Trust region policy optimization
Schulman, John, Levine, Sergey, Abbeel, Pieter, Jordan, Michael, and Moritz, Philipp · 2015
Cited alongside, same era.
Brockman, Greg, Cheung, Vicki, Pettersson, Ludwig, Schneider, Jonas, Schulman, John, Tang, Jie, and Zaremba, Wojciech · 2016
Cited alongside, same era.
Transfer from simulation to real world through learning deep inverse dynamics model
Christiano, Paul, Shah, Zain, Mordatch, Igor, Schneider, Jonas, Blackwell, Trevor, Tobin, Joshua, Abbeel, Pieter, and Zaremba, Wojciech · 2016
Cited alongside, same era.
Benchmarking deep reinforcement learning for continuous control
Duan, Yan, Chen, Xi, Houthooft, Rein, Schulman, John, and Abbeel, Pieter · 2016
Cited alongside, same era.
Generalizing skills with semi-supervised reinforcement learning
Finn, Chelsea, Yu, Tianhe, Fu, Justin, Abbeel, Pieter, and Levine, Sergey · 2016
Reinforcement learning with unsupervised auxiliary tasks
Jaderberg, Max, Mnih, Volodymyr, Czarnecki, Wojciech Marian, Schaul, Tom, Leibo, Joel Z, Silver, David, and Kavukcuoglu, Koray · 2016
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Adaptive smoothed online multi-task learning
Murugesan, Keerthiram, Liu, Hanxiao, Carbonell, Jaime, and Yang, Yiming · 2016
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Sim-to-real robot learning from pixels with progressive nets
Rusu, Andrei A, Vecerik, Matej, Rothörl, Thomas, Heess, Nicolas, Pascanu, Razvan, and Hadsell, Raia · 2016
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Value Iteration Networks
Tamar, A., Wu, Y., Thomas, G., Levine, S., and Abbeel, P · 2016
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Learning invariant feature spaces to transfer skills with reinforcement learning
Gupta, Abhishek, Devin, Coline, Liu, YuXuan, Abbeel, Pieter, and Levine, Sergey · 2017
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Cited alongside, same era.
Q-prop: Sample-efficient policy gradient with an off-policy critic
Gu, Shixiang, Lillicrap, Timothy, Ghahramani, Zoubin, Turner, Richard E., and Levine, Sergey · 2016
Cited alongside, same era.
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Adapting learned robotics behaviours through policy adjustment
Higuera, Juan Camilo Gamboa, Meger, David, and Dudek, Gregory · 2017
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