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In imitation learning, an agent learns how to behave in an environment with an unknown cost function by mimicking expert demonstrations.
Efficient training of artificial neural networks for autonomous navigation
Pomerleau, Dean A · 1991
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Simple statistical gradient-following algorithms for connectionist reinforcement learning
Williams, Ronald J · 1992
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Learning agents for uncertain environments
Russell, Stuart · 1998
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Policy gradient methods for reinforcement learning with function approximation
Sutton, Richard S, McAllester, David A, Singh, Satinder P, and Mansour, Yishay · 1999
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Algorithms for inverse reinforcement learning
Ng, Andrew Y and Russell, Stuart J · 2000
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Approximately optimal approximate reinforcement learning
Kakade, Sham and Langford, John · 2002
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Apprenticeship learning via inverse reinforcement learning
Abbeel, Pieter and Ng, Andrew Y · 2004
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Maximum margin planning
Ratliff, Nathan D, Bagnell, J Andrew, and Zinkevich, Martin A · 2006
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A game-theoretic approach to apprenticeship learning
Syed, Umar and Schapire, Robert E · 2007
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Reinforcement learning of motor skills with policy gradients
Peters, Jan and Schaal, Stefan · 2008
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Apprenticeship learning using linear programming
Syed, Umar, Bowling, Michael, and Schapire, Robert E · 2008
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Maximum entropy inverse reinforcement learning
Ziebart, Brian D, Maas, Andrew L, Bagnell, J Andrew, and Dey, Anind K · 2008
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Search-based structured prediction
Daumé III, Hal, Langford, John, and Marcu, Daniel · 2009
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Training parsers by inverse reinforcement learning
Neu, Gergely and Szepesvári, Csaba · 2009
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Learning to search: Functional gradient techniques for imitation learning
Ratliff, Nathan D, Silver, David, and Bagnell, J Andrew · 2009
A reduction of imitation learning and structured prediction to no-regret online learning
Ross, Stéphane, Gordon, Geoffrey J, and Bagnell, Drew · 2011
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Continuous inverse optimal control with locally optimal examples
Levine, Sergey and Koltun, Vladlen · 2012
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Learning from limited demonstrations
Kim, Beomjoon, Farahmand, Amir-massoud, Pineau, Joelle, and Precup, Doina · 2013
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Generative adversarial nets
Goodfellow, Ian, Pouget-Abadie, Jean, Mirza, Mehdi, Xu, Bing, Warde-Farley, David, Ozair, Sherjil, Courville, Aaron, and Bengio, Yoshua · 2014
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An invitation to imitation
Bagnell, J Andrew · 2015
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Learning large-scale dynamic discrete choice models of spatio-temporal preferences with application to migratory pastoralism in East Africa
Ermon, Stefano, Xue, Yexiang, Toth, Russell, Dilkina, Bistra N, Bernstein, Richard, Damoulas, Theodoros, Clark, Patrick, DeGloria, Steve, Mude, Andrew, Barrett, Christopher, et al · 2015
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A reduction from apprenticeship learning to classification
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