Robotics paper list

Posted 2015.10.06 14:27
Related Paper List



Jaakkola, Tommi, Michael I. Jordan, and Satinder P. Singh. "On the convergence of stochastic iterative dynamic programming algorithms." Neural computation 6.6 (1994) - 
- http://www.mitpressjournals.org/doi/pdfplus/10.1162/neco.1994.6.6.1185 "KJ"

Bertsekas, Dimitri P., and Dimitri P. Bertsekas. Dynamic programming and optimal control - Ch6 Approximate Dynamic programming. Vol. 1. No. 2. Belmont, MA: Athena Scientific, 1995.
- http://web.mit.edu/dimitrib/www/dpchapter.pdf "KJ"

Andrew Y. Ng, and Stuart J. Russell. "Algorithms for Inverse Reinforcement Learning." ICML 2000.
- http://ai.stanford.edu/~ang/papers/icml00-irl.pdf "KJ"

Baxter, Jonathan, and Peter L. Bartlett. "Infinite-horizon policy-gradient estimation." Journal of Artificial Intelligence Research (2001)
- http://www.jair.org/media/806/live-806-1942-jair.pdf

Kakade, Sham, and John Langford. "Approximately optimal approximate reinforcement learning." ICML. Vol. 2. 2002.
- http://www.cs.cmu.edu/~./jcl/papers/aoarl/Final.pdf

Kakade, Sham Machandranath. On the sample complexity of reinforcement learning. Diss. University of London, 2003.
- http://www.ias.tu-darmstadt.de/uploads/Research/NIPS2006/SK.pdf

Lagoudakis, Michail G., and Ronald Parr. "Least-squares policy iteration." The Journal of Machine Learning Research 4 (2003): 1107-1149.
- http://machinelearning.wustl.edu/mlpapers/paper_files/LagoudakisP03.pdf "KJ"

Abbeel, Pieter, and Andrew Y. Ng. "Apprenticeship Learning via Inverse Reinforcement Learning." ICML 2004.

- http://machinelearning.wustl.edu/mlpapers/paper_files/icml2004_PieterN04.pdf

Greensmith, Evan, Peter L. Bartlett, and Jonathan Baxter. "Variance reduction techniques for gradient estimates in reinforcement learning." JMLR (2004): 1471-1530.
- http://machinelearning.wustl.edu/mlpapers/paper_files/GreensmithBB04.pdf "KJ"

Abbeel, Pieter, and Andrew Y. Ng. "Exploration and Apprenticeship Learning in Reinforcement Learning." ICML 2005.

- http://machinelearning.wustl.edu/mlpapers/paper_files/icml2005_AbbeelN05.pdf "KJ"


Ramachandran, Deepak, and Eyal Amir. "Bayesian Inverse Reinforcement Learning." AAAI 2007.

- http://www.aaai.org/Papers/IJCAI/2007/IJCAI07-416.pdf 


Peters, Jan, and Stefan Schaal. "Reinforcement learning of motor skills with policy gradients." Neural networks 21.4 (2008)

- http://www.keck.ucsf.edu/~houde/sensorimotor_jc/possible_papers/JPeters08a.pdf


Brian D. Ziebart, Andrew Maas, J.Andrew Bagnell, and Anind K. Dey, "Maximum Entropy Inverse Reinforcement Learning." AAAI. 2008.

- http://www.aaai.org/Papers/AAAI/2008/AAAI08-227.pdf


Daumé Iii, Hal, John Langford, and Daniel Marcu. "Search-based structured prediction." Machine learning 75.3 (2009): 297-325.

- http://arxiv.org/pdf/0907.0786.pdf "KJ"


Ross, Stéphane, Geoffrey J. Gordon, and J. Andrew Bagnell. "A reduction of imitation learning and structured prediction to no-regret online learning." arXiv preprint arXiv:1011.0686 (2010).

- http://arxiv.org/pdf/1011.0686.pdf "KJ"


Scherrer, Bruno, et al. "Approximate modified policy iteration." arXiv preprint arXiv:1205.3054 (2012).

- http://arxiv.org/pdf/1205.3054.pdf


Dimitrakakis, Christos, and Constantin A. Rothkopf. "Bayesian Multitask Inverse Reinforcement Learning." Recent Advances in Reinforcement Learning. 2012

- http://arxiv.org/pdf/1106.3655.pdf


Choi, Jaedeug, and Kee-Eung Kim. "Nonparametric Bayesian Inverse Reinforcement Learning for Multiple Reward Functions." NIPS 2012.

- http://papers.nips.cc/paper/4737-nonparametric-bayesian-inverse-reinforcement-learning-for-multiple-reward-functions.pdf "KJ"


Levine, Sergey, and Vladlen Koltun. "Guided Policy Search." ICML 2013.

- http://jmlr.org/proceedings/papers/v28/levine13.pdf


Ross, Stéphane. Interactive Learning for Sequential Decisions and Predictions. Diss. CARNEGIE MELLON UNIVERSITY, 2013.

- http://www.cs.cmu.edu/~sross1/phd_thesis.pdf


Ross, Stéphane, and J. Andrew Bagnell. "Reinforcement and imitation learning via interactive no-regret learning." arXiv preprint arXiv:1406.5979 (2014).

- http://arxiv.org/pdf/1406.5979.pdf "KJ"


Guo, Xiaoxiao, Satinder Singh, Honglak Lee, Richard Lewis, Xiaoshi Wang. "Deep learning for real-time Atari game play using offline Monte-Carlo tree search planning." Advances in Neural Information Processing Systems. 2014.

http://papers.nips.cc/paper/5421-deep-learning-for-real-time-atari-game-play-using-offline-monte-carlo-tree-search-planning.pdf


Levine, Sergey, and Vladlen Koltun. "Learning complex neural network policies with trajectory optimization." ICML 2014.

- http://graphics.stanford.edu/projects/cgpspaper/cgps.pdf

- http://graphics.stanford.edu/projects/cgpspaper/index.htm


Levine, Sergey, and Pieter Abbeel. "Learning neural network policies with guided policy search under unknown dynamics." NIPS 2014.

- http://www.eecs.berkeley.edu/~svlevine/papers/mfcgps.pdf "KJ"


Mordatch, Igor, and Emanuel Todorov. "Combining the benefits of function approximation and trajectory optimization." Robotics: Science and Systems (RSS). 2014.

- http://www.roboticsproceedings.org/rss10/p52.pdf "KJ"


Levine, Sergey, Nolan Wagener, and Pieter Abbeel. "Learning Contact-Rich Manipulation Skills with Guided Policy Search." ICRA 2015.

- http://arxiv.org/pdf/1501.05611v2.pdf


Dylan Hadfield-Menell, Edward Groshev, Rohan Chitnis, and Pieter Abbeel. "Modular Task and Motion Planning in Belief Space." IROS 2015

http://www.cs.berkeley.edu/~pabbeel/papers/2015-IROS-TMP-belief-space.pdf "KJ"


Han, Weiqiao, Sergey Levine, and Pieter Abbeel. "Learning Compound Multi-Step Controllers under Unknown Dynamics.", IROS 2015

- http://rll.berkeley.edu/reset_controller/reset_controller.pdf

- http://rll.berkeley.edu/reset_controller/


Alex X. Lee Abhishek Gupta Henry Lu Sergey Levine Pieter Abbeel. "Learning from Multiple Demonstrations using Trajectory-Aware Non-Rigid Registration with Applications to Deformable Object Manipulation." IROS 2015

- http://www.cs.berkeley.edu/~pabbeel/papers/2015-IROS-trajectory-aware-registration.pdf "KJ"


Sergey Levine, Chelsea Finn, Trevor Darrell, Pieter Abbeel "End-to-End Training of Deep Visuomotor Policies." arXiv preprint arXiv:1504.00702 (2015).

- http://arxiv.org/pdf/1504.00702v1.pdf


John Schulman, Sergey Levine, Philipp Moritz, Michael I. Jordan, Pieter Abbeel. "Trust Region Policy Optimization." arXiv preprint arXiv:1502.05477 (2015).

- http://arxiv.org/pdf/1502.05477v3.pdf


Fu, Justin, Sergey Levine, and Pieter Abbeel. "One-Shot Learning of Manipulation Skills with Online Dynamics Adaptation and Neural Network Priors." arXiv preprint arXiv:1509.06841 (2015).

- http://rll.berkeley.edu/icra2016onlinecontrol/online_control.pdf


Chelsea Finn, Xin Yu Tan, Yan Duan, Trevor Darrell, Sergey Levine, Pieter Abbeel "Learning Visual Feature Spaces for Robotic Manipulation with Deep Spatial Autoencoders." arXiv preprint arXiv:1509.06113 (2015).

- http://arxiv.org/pdf/1509.06113v1.pdf


Marvin Zhang, Zoe McCarthy, Chelsea Finn, Sergey Levine, Pieter Abbeel. "Learning Deep Control Policies for Autonomous Aerial Vehicles with MPC-Guided Policy Search." arXiv preprint arXiv:1509.06791 (2015).

- http://rll.berkeley.edu/icra2016mpcgps/ICRA16_MPCGPS "KJ"


Christopher Xie, Sachin Patil, Teodor Moldovan, Sergey Levine, Pieter Abbeel "Model-based Reinforcement Learning with Parametrized Physical Models and Optimism-Driven Exploration." arXiv preprint arXiv:1509.06824 (2015).

- http://arxiv.org/pdf/1509.06824v1.pdf "KJ"



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