Learning Robot Skill Embeddings
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Karol Hausman | Martin A. Riedmiller | Jost Tobias Springenberg | Ziyu Wang | Nicolas Heess | Martin Riedmiller | Ziyun Wang | N. Heess | Karol Hausman | J. T. Springenberg
[1] N. Roy,et al. On Stochastic Optimal Control and Reinforcement Learning by Approximate Inference , 2013 .
[2] Yuval Tassa,et al. Learning human behaviors from motion capture by adversarial imitation , 2017, ArXiv.
[3] Yee Whye Teh,et al. Distral: Robust multitask reinforcement learning , 2017, NIPS.
[4] Doina Precup,et al. The Option-Critic Architecture , 2016, AAAI.
[5] Nando de Freitas,et al. Robust Imitation of Diverse Behaviors , 2017, NIPS.
[6] Shane Legg,et al. Human-level control through deep reinforcement learning , 2015, Nature.
[7] Sergey Levine,et al. Variational Policy Search via Trajectory Optimization , 2013, NIPS.
[8] Sergey Levine,et al. Reinforcement Learning with Deep Energy-Based Policies , 2017, ICML.
[9] David Barber,et al. The IM algorithm: a variational approach to Information Maximization , 2003, NIPS 2003.
[10] Gaurav S. Sukhatme,et al. Multi-Modal Imitation Learning from Unstructured Demonstrations using Generative Adversarial Nets , 2017, NIPS.
[11] Sepp Hochreiter,et al. Fast and Accurate Deep Network Learning by Exponential Linear Units (ELUs) , 2015, ICLR.
[12] Misha Denil,et al. The Intentional Unintentional Agent: Learning to Solve Many Continuous Control Tasks Simultaneously , 2017, CoRL.
[13] Gerhard Neumann,et al. Variational Inference for Policy Search in changing situations , 2011, ICML.
[14] Shakir Mohamed,et al. Variational Information Maximisation for Intrinsically Motivated Reinforcement Learning , 2015, NIPS.
[15] Stefano Ermon,et al. Inferring The Latent Structure of Human Decision-Making from Raw Visual Inputs , 2017, NIPS 2017.
[16] R. J. Williams,et al. Simple Statistical Gradient-Following Algorithms for Connectionist Reinforcement Learning , 2004, Machine Learning.
[17] Yuval Tassa,et al. Learning and Transfer of Modulated Locomotor Controllers , 2016, ArXiv.
[18] Yee Whye Teh,et al. The Concrete Distribution: A Continuous Relaxation of Discrete Random Variables , 2016, ICLR.
[19] Sergey Levine,et al. Trust Region Policy Optimization , 2015, ICML.
[20] Roy Fox,et al. Taming the Noise in Reinforcement Learning via Soft Updates , 2015, UAI.
[21] Anil A. Bharath,et al. Deep Reinforcement Learning: A Brief Survey , 2017, IEEE Signal Processing Magazine.
[22] Max Welling,et al. Auto-Encoding Variational Bayes , 2013, ICLR.
[23] Max Welling,et al. Markov Chain Monte Carlo and Variational Inference: Bridging the Gap , 2014, ICML.
[24] Sergey Levine,et al. Learning modular neural network policies for multi-task and multi-robot transfer , 2016, 2017 IEEE International Conference on Robotics and Automation (ICRA).
[25] Ben Poole,et al. Categorical Reparameterization with Gumbel-Softmax , 2016, ICLR.
[26] Daan Wierstra,et al. Stochastic Backpropagation and Approximate Inference in Deep Generative Models , 2014, ICML.
[27] Pieter Abbeel,et al. Equivalence Between Policy Gradients and Soft Q-Learning , 2017, ArXiv.
[28] Emanuel Todorov,et al. General duality between optimal control and estimation , 2008, 2008 47th IEEE Conference on Decision and Control.
[29] Marc Toussaint,et al. Robot trajectory optimization using approximate inference , 2009, ICML '09.
[30] Sergey Levine,et al. Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks , 2017, ICML.
[31] Marc G. Bellemare,et al. Safe and Efficient Off-Policy Reinforcement Learning , 2016, NIPS.
[32] Daan Wierstra,et al. Variational Intrinsic Control , 2016, ICLR.
[33] Pieter Abbeel,et al. Stochastic Neural Networks for Hierarchical Reinforcement Learning , 2016, ICLR.
[34] Alex Graves,et al. Asynchronous Methods for Deep Reinforcement Learning , 2016, ICML.
[35] Sergey Levine,et al. End-to-End Training of Deep Visuomotor Policies , 2015, J. Mach. Learn. Res..
[36] Dustin Tran,et al. Hierarchical Variational Models , 2015, ICML.
[37] Ole Winther,et al. Auxiliary Deep Generative Models , 2016, ICML.
[38] Yuval Tassa,et al. Learning Continuous Control Policies by Stochastic Value Gradients , 2015, NIPS.
[39] Razvan Pascanu,et al. Overcoming catastrophic forgetting in neural networks , 2016, Proceedings of the National Academy of Sciences.
[40] J. Andrew Bagnell,et al. Modeling Purposeful Adaptive Behavior with the Principle of Maximum Causal Entropy , 2010 .