机器人 / 具身智能 - arXivDaily 专题

1805.04686 2019-02-19 cs.LG cs.RO stat.ML 62%

Task Transfer by Preference-Based Cost Learning

Mingxuan Jing, Xiaojian Ma, Wenbing Huang, Fuchun Sun, Huaping Liu

专题命中模仿学习与强化学习：robotic(abstract)；分类 cs.RO、cs.LG

Comments Accepted to AAAI 2019. Mingxuan Jing and Xiaojian Ma contributed equally to this work

1902.04546 2019-02-13 cs.LG cs.AI cs.NE stat.ML 62%

ACTRCE: Augmenting Experience via Teacher's Advice For Multi-Goal Reinforcement Learning

Harris Chan, Yuhuai Wu, Jamie Kiros, Sanja Fidler, Jimmy Ba

专题命中模仿学习与强化学习：navigation(abstract)；分类 cs.AI、cs.LG

1901.10031 2019-02-13 cs.LG cs.AI stat.ML 62%

Lyapunov-based Safe Policy Optimization for Continuous Control

Yinlam Chow, Ofir Nachum, Aleksandra Faust, Edgar Duenez-Guzman, Mohammad Ghavamzadeh

专题命中模仿学习与强化学习：navigation(abstract)；分类 cs.AI、cs.LG

1902.01554 2019-02-06 cs.AI cs.LG cs.MA 62%

Learning to Schedule Communication in Multi-agent Reinforcement Learning

Daewoo Kim, Sangwoo Moon, David Hostallero, Wan Ju Kang, Taeyoung Lee, Kyunghwan Son, Yung Yi

专题命中模仿学习与强化学习：navigation(abstract)；分类 cs.AI、cs.LG

Comments Accepted in ICLR 2019

1901.01994 2019-01-21 cs.LG cs.AI stat.ML 62%

Recurrent Control Nets for Deep Reinforcement Learning

Vincent Liu, Ademi Adeniji, Nathaniel Lee, Jason Zhao, Mario Srouji

专题命中模仿学习与强化学习：robotics(abstract)；分类 cs.AI、cs.LG

1812.09968 2018-12-27 cs.LG cs.AI cs.NE 62%

VMAV-C: A Deep Attention-based Reinforcement Learning Algorithm for Model-based Control

Xingxing Liang, Qi Wang, Yanghe Feng, Zhong Liu, Jincai Huang

专题命中模仿学习与强化学习：world model(abstract)；分类 cs.AI、cs.LG

1812.00025 2018-12-04 cs.LG cs.AI 62%

Modulated Policy Hierarchies

Alexander Pashevich, Danijar Hafner, James Davidson, Rahul Sukthankar, Cordelia Schmid

专题命中模仿学习与强化学习：robotics(abstract)；分类 cs.AI、cs.LG

Comments 8 pages, 5 figures

1811.12560 2018-12-04 cs.LG cs.AI stat.ML 62%

An Introduction to Deep Reinforcement Learning

Vincent Francois-Lavet, Peter Henderson, Riashat Islam, Marc G. Bellemare, Joelle Pineau

专题命中模仿学习与强化学习：robotics(abstract)；分类 cs.AI、cs.LG

Journal ref Foundations and Trends in Machine Learning: Vol. 11, No. 3-4, 2018

1710.11424 2018-10-26 cs.LG cs.AI 62%

Regret Minimization for Partially Observable Deep Reinforcement Learning

Peter Jin, Kurt Keutzer, Sergey Levine

专题命中模仿学习与强化学习：navigation(abstract)；分类 cs.AI、cs.LG

Comments ICML 2018

1802.06070 2018-10-11 cs.AI cs.RO 62%

Diversity is All You Need: Learning Skills without a Reward Function

Benjamin Eysenbach, Abhishek Gupta, Julian Ibarz, Sergey Levine

专题命中模仿学习与强化学习：robotic(abstract)；分类 cs.RO、cs.AI

Comments Videos and code for our experiments are available at: https://sites.google.com/view/diayn

1805.08296 2018-10-08 cs.LG cs.AI stat.ML 62%

Data-Efficient Hierarchical Reinforcement Learning

Ofir Nachum, Shixiang Gu, Honglak Lee, Sergey Levine

专题命中模仿学习与强化学习：robotic(abstract)；分类 cs.AI、cs.LG

Comments NIPS 2018

1810.00361 2018-10-02 cs.LG cs.AI stat.ML 62%

Using State Predictions for Value Regularization in Curiosity Driven Deep Reinforcement Learning

Gino Brunner, Manuel Fritsche, Oliver Richter, Roger Wattenhofer

专题命中模仿学习与强化学习：navigation(abstract)；分类 cs.AI、cs.LG

1809.06064 2018-09-18 cs.LG cs.CV stat.ML 62%

Object-sensitive Deep Reinforcement Learning

Yuezhang Li, Katia Sycara, Rahul Iyer

专题命中模仿学习与强化学习：navigation(abstract)；分类 cs.CV、cs.LG

Comments 15 pages, 6 figures, Accepted at 3rd Global Conference on Artificial Intelligence (GCAI-17), Miami, 2017

1803.02291 2018-08-02 cs.RO cs.AI 62%

Synthesizing Neural Network Controllers with Probabilistic Model based Reinforcement Learning

Juan Camilo Gamboa Higuera, David Meger, Gregory Dudek

专题命中模仿学习与强化学习：robotics(abstract)；分类 cs.RO、cs.AI

Comments 8 pages, 7 figures

1807.09205 2018-07-25 cs.RO cs.AI 62%

End-to-End Deep Imitation Learning: Robot Soccer Case Study

Okan Aşık, Binnur Görer, H. Levent Akın

专题命中模仿学习与强化学习：robotics(abstract)；分类 cs.RO、cs.AI

Comments RoboCup 2018 Symposium

1807.07530 2018-07-20 cs.LG cs.AI stat.ML 62%

Self-Organizing Maps as a Storage and Transfer Mechanism in Reinforcement Learning

Thommen George Karimpanal, Roland Bouffanais

专题命中模仿学习与强化学习：navigation(abstract)；分类 cs.AI、cs.LG

Comments 7 pages, 7 figures, presented at ALA Workshop, FAIM, Stockholm, 2018

1805.08882 2018-07-17 cs.LG cs.AI stat.ML 62%

Multi-task Maximum Entropy Inverse Reinforcement Learning

Adam Gleave, Oliver Habryka

专题命中模仿学习与强化学习：robotics(abstract)；分类 cs.AI、cs.LG

Comments Presented at 1st Workshop on Goal Specifications for Reinforcement Learning (ICML/IJCAI/AAMAS 2018)

1807.03776 2018-07-11 cs.CV cs.RO 62%

CIRL: Controllable Imitative Reinforcement Learning for Vision-based Self-driving

Xiaodan Liang, Tairui Wang, Luona Yang, Eric Xing

专题命中模仿学习与强化学习：navigation(abstract)；分类 cs.RO、cs.CV

Comments To appear in ECCV 2018

1802.06139 2018-06-29 cs.AI cs.LG 62%

Reactive Reinforcement Learning in Asynchronous Environments

Jaden B. Travnik, Kory W. Mathewson, Richard S. Sutton, Patrick M. Pilarski

专题命中模仿学习与强化学习：robotic(abstract)；分类 cs.AI、cs.LG

Comments 11 pages, 7 figures, currently under journal peer review

1707.00724 2018-06-26 cs.AI cs.LG stat.ML 62%

Efficient Probabilistic Performance Bounds for Inverse Reinforcement Learning

Daniel S. Brown, Scott Niekum

专题命中模仿学习与强化学习：navigation(abstract)；分类 cs.AI、cs.LG

Comments In proceedings AAAI-18

1703.09700 2018-06-26 cs.LG cs.AI stat.ML 62%

Inverse Reinforcement Learning from Summary Data

Antti Kangasrääsiö, Samuel Kaski

专题命中模仿学习与强化学习：world model(abstract)；分类 cs.AI、cs.LG

Comments To appear in ECMLPKDD'2018

1806.06569 2018-06-19 cs.AI cs.RO 62%

Learning from Outside the Viability Kernel: Why we Should Build Robots that can Fall with Grace

Steve Heim, Alexander Spröwitz

专题命中模仿学习与强化学习：robotics(abstract)；分类 cs.RO、cs.AI

Comments Proceedings of the 2018 IEEE International Conference on SImulation, Modeling and Programming for Autonomous Robots (SIMPAR), Brisbane, Australia, 16-19 2018

1804.02395 2018-06-13 cs.LG cs.RO stat.ML 62%

Structured Evolution with Compact Architectures for Scalable Policy Optimization

Krzysztof Choromanski, Mark Rowland, Vikas Sindhwani, Richard E. Turner, Adrian Weller

专题命中模仿学习与强化学习：robotics(abstract)；分类 cs.RO、cs.LG

1802.04325 2018-06-12 cs.LG cs.AI stat.ML 62%

Efficient Model-Based Deep Reinforcement Learning with Variational State Tabulation

Dane Corneil, Wulfram Gerstner, Johanni Brea

专题命中模仿学习与强化学习：navigation(abstract)；分类 cs.AI、cs.LG

Comments Accepted at ICML 2018; camera-ready version

1806.01368 2018-06-06 cs.RO cs.AI 62%

Adversarial Reinforcement Learning Framework for Benchmarking Collision Avoidance Mechanisms in Autonomous Vehicles

Vahid Behzadan, Arslan Munir

专题命中模仿学习与强化学习：navigation(abstract)；分类 cs.RO、cs.AI

1805.02785 2018-05-18 cs.LG cs.AI stat.ML 62%

Fast Online Exact Solutions for Deterministic MDPs with Sparse Rewards

Joshua R. Bertram, Xuxi Yang, Peng Wei

专题命中模仿学习与强化学习：robotics(abstract)；分类 cs.AI、cs.LG

Comments Submitted to NIPS 2018; preprint version posted here. 8 pages content, appendices include pseudocode and proof for algorithm

1804.10692 2018-05-01 cs.CV cs.RO 62%

Reward Learning from Narrated Demonstrations

Hsiao-Yu Fish Tung, Adam W. Harley, Liang-Kang Huang, Katerina Fragkiadaki

专题命中模仿学习与强化学习：robotic(abstract)；分类 cs.RO、cs.CV

Comments The work has been accepted to Conference on Computer Vision and Pattern Recognition (CVPR) 2018

1711.09874 2018-04-30 cs.LG cs.RO 62%

Divide-and-Conquer Reinforcement Learning

Dibya Ghosh, Avi Singh, Aravind Rajeswaran, Vikash Kumar, Sergey Levine

专题命中模仿学习与强化学习：manipulation(abstract)；分类 cs.RO、cs.LG

Comments Presented at ICLR 2018. Videos and supporting materials are located at http://bit.ly/dnc-rl

1704.06888 2018-03-21 cs.CV cs.RO 62%

Time-Contrastive Networks: Self-Supervised Learning from Video

Pierre Sermanet, Corey Lynch, Yevgen Chebotar, Jasmine Hsu, Eric Jang, Stefan Schaal, Sergey Levine

专题命中模仿学习与强化学习：robotic(abstract)；分类 cs.RO、cs.CV

1803.01489 2018-03-06 stat.ML cs.AI cs.LG 62%

Recurrent Predictive State Policy Networks

Ahmed Hefny, Zita Marinho, Wen Sun, Siddhartha Srinivasa, Geoffrey Gordon

专题命中模仿学习与强化学习：robotic(abstract)；分类 cs.AI、cs.LG

1. 模仿学习与强化学习 4115 篇

Task Transfer by Preference-Based Cost Learning

ACTRCE: Augmenting Experience via Teacher's Advice For Multi-Goal Reinforcement Learning

Lyapunov-based Safe Policy Optimization for Continuous Control

Learning to Schedule Communication in Multi-agent Reinforcement Learning

Recurrent Control Nets for Deep Reinforcement Learning

VMAV-C: A Deep Attention-based Reinforcement Learning Algorithm for Model-based Control

Modulated Policy Hierarchies

An Introduction to Deep Reinforcement Learning

Regret Minimization for Partially Observable Deep Reinforcement Learning

Diversity is All You Need: Learning Skills without a Reward Function

Data-Efficient Hierarchical Reinforcement Learning

Using State Predictions for Value Regularization in Curiosity Driven Deep Reinforcement Learning

Object-sensitive Deep Reinforcement Learning

Synthesizing Neural Network Controllers with Probabilistic Model based Reinforcement Learning

End-to-End Deep Imitation Learning: Robot Soccer Case Study

Self-Organizing Maps as a Storage and Transfer Mechanism in Reinforcement Learning

Multi-task Maximum Entropy Inverse Reinforcement Learning

CIRL: Controllable Imitative Reinforcement Learning for Vision-based Self-driving

Reactive Reinforcement Learning in Asynchronous Environments

Efficient Probabilistic Performance Bounds for Inverse Reinforcement Learning

Inverse Reinforcement Learning from Summary Data

Learning from Outside the Viability Kernel: Why we Should Build Robots that can Fall with Grace

Structured Evolution with Compact Architectures for Scalable Policy Optimization

Efficient Model-Based Deep Reinforcement Learning with Variational State Tabulation

Adversarial Reinforcement Learning Framework for Benchmarking Collision Avoidance Mechanisms in Autonomous Vehicles

Fast Online Exact Solutions for Deterministic MDPs with Sparse Rewards

Reward Learning from Narrated Demonstrations

Divide-and-Conquer Reinforcement Learning

Time-Contrastive Networks: Self-Supervised Learning from Video

Recurrent Predictive State Policy Networks