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This works handles the inverse reinforcement learning problem in high-dimensional state spaces, which relies on an efficient solution of model-based high-dimensional reinforcement learning problems.
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B. D. Ziebart, A. Maas, J. A. Bagnell, and A. K. Dey, “Maximum entropy inverse reinforcement learning,” in Proc. AAAI , 2008, pp. 1433–1438
2008
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K. Mombaur, A. Truong, and J.-P. Laumond, “From human to humanoid locomotion—an inverse optimal control approach,” Autonomous robots , vol. 28, no. 3, pp. 369–383, 2010
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S. Levine, Z. Popovic, and V. Koltun, “Nonlinear inverse reinforcement learning with gaussian processes,” in Advances in Neural Information Processing Systems 24 , J. Shawe-Taylor, R. S. Zemel, P. L. Bartlett, F. Pereira, and K. Q. Weinberger, Eds. Curran Associates, Inc., 2011, pp. 19–27
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J. Choi and K.-E. Kim, “Inverse reinforcement learning in partially observable environments,” Journal of Machine Learning Research , vol. 12, no. Mar, pp. 691–730, 2011
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J. Choi and K.-E. Kim, “Nonparametric bayesian inverse reinforcement learning for multiple reward functions,” in Advances in Neural Information Processing Systems , 2012, pp. 305–313
2012
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2013
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Y. Gao, S. S. Vedula, C. E. Reiley, N. Ahmidi, B. Varadarajan, H. C. Lin, L. Tao, L. Zappella, B. Béjar, D. D. Yuh et al. , “Jhu-isi gesture and skill assessment working set (jigsaws): A surgical activity dataset for human motion modeling,” in MICCAI Workshop: M2CAI , vol. 3, 2014
2014
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Q. P. Nguyen, B. K. H. Low, and P. Jaillet, “Inverse reinforcement learning with locally consistent reward functions,” in Advances in Neural Information Processing Systems , 2015, pp. 1747–1755
2015
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C. Dimitrakakis and C. A. Rothkopf, “Bayesian multitask inverse reinforcement learning,” in European Workshop on Reinforcement Learning . Springer, 2011, pp. 273–284
2011
Cited alongside, same era.
A. Boularias, J. Kober, and J. R. Peters, “Relative entropy inverse reinforcement learning,” in International Conference on Artificial Intelligence and Statistics , 2011, pp. 182–189
2011
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2012
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2012
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2015
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2016
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K. Li and J. W. Burdick, “Bellman Gradient Iteration for Inverse Reinforcement Learning,” ArXiv e-prints , Jul. 2017
2017
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H. v. Hasselt, A. Guez, and D. Silver, “Deep reinforcement learning with double q-learning,” in Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence . AAAI Press, 2016, pp. 2094–2100
2094
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