机器人 / 具身智能 - arXivDaily 专题

2103.13267 2021-03-25 cs.RO cs.LG 62%

CLAMGen: Closed-Loop Arm Motion Generation via Multi-view Vision-Based RL

Iretiayo Akinola, Zizhao Wang, Peter Allen

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

2103.09756 2021-03-18 cs.LG cs.AI 62%

Near Optimal Policy Optimization via REPS

Aldo Pacchiano, Jonathan Lee, Peter Bartlett, Ofir Nachum

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

Comments 8 main pages, 37 total pages

1904.10762 2021-03-17 cs.LG cs.AI stat.ML 62%

Baconian: A Unified Open-source Framework for Model-Based Reinforcement Learning

Linsen Dong, Guanyu Gao, Xinyi Zhang, Liangyu Chen, Yonggang Wen

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

1910.08143 2021-03-16 cs.LG cs.AI stat.ML 62%

Zero-shot Policy Learning with Spatial Temporal RewardDecomposition on Contingency-aware Observation

Huazhe Xu, Boyuan Chen, Yang Gao, Trevor Darrell

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

2103.05079 2021-03-10 cs.LG cs.AI 62%

Domain-Robust Visual Imitation Learning with Mutual Information Constraints

Edoardo Cetin, Oya Celiktutan

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

Comments Presented at ICLR 2021

2011.14487 2021-03-09 cs.RO cs.AI 62%

Continuous Transition: Improving Sample Efficiency for Continuous Control Problems via MixUp

Junfan Lin, Zhongzhan Huang, Keze Wang, Xiaodan Liang, Weiwei Chen, Liang Lin

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

2006.09324 2021-03-09 cs.LG cs.AI stat.ML 62%

The Sample Complexity of Teaching-by-Reinforcement on Q-Learning

Xuezhou Zhang, Shubham Kumar Bharti, Yuzhe Ma, Adish Singla, Xiaojin Zhu

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

2103.01991 2021-03-04 cs.LG cs.AI cs.MA 62%

Adversarial Environment Generation for Learning to Navigate the Web

Izzeddin Gur, Natasha Jaques, Kevin Malta, Manoj Tiwari, Honglak Lee, Aleksandra Faust

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

Comments Presented at Deep RL Workshop, NeurIPS, 2020

2102.10357 2021-02-23 cs.RO cs.LG 62%

How To Train Your HERON

Antoine Richard, Stephanie Aravecchia, Thomas Schillaci, Matthieu Geist, Cedric Pradalier

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

2102.02872 2021-02-12 cs.LG cs.RO stat.ML 62%

Feedback in Imitation Learning: The Three Regimes of Covariate Shift

Jonathan Spencer, Sanjiban Choudhury, Arun Venkatraman, Brian Ziebart, J. Andrew Bagnell

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

2102.02639 2021-02-05 cs.LG cs.AI cs.HC 62%

Improving Reinforcement Learning with Human Assistance: An Argument for Human Subject Studies with HIPPO Gym

Matthew E. Taylor, Nicholas Nissen, Yuan Wang, Neda Navidi

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

2011.06192 2021-02-05 cs.RO cs.LG 62%

Motion Generation Using Bilateral Control-Based Imitation Learning with Autoregressive Learning

Ayumu Sasagawa, Sho Sakaino, Toshiaki Tsuji

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

Comments Copyright 2021 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works

Journal ref IEEE Access, Volume 9, Pages 20508-20520, 2021

1910.11689 2021-01-26 cs.RO cs.AI 62%

Collision Avoidance in Pedestrian-Rich Environments with Deep Reinforcement Learning

Michael Everett, Yu Fan Chen, Jonathan P. How

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

Comments arXiv admin note: substantial text overlap with arXiv:1805.01956

2101.02649 2021-01-08 cs.LG cs.RO 62%

CoachNet: An Adversarial Sampling Approach for Reinforcement Learning

Elmira Amirloo Abolfathi, Jun Luo, Peyman Yadmellat, Kasra Rezaee

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

Comments NeurIPS2019 Workshop on Safety and Robustness in Decision Making

2101.01055 2021-01-05 cs.LG cs.RO 62%

Stochastic Action Prediction for Imitation Learning

Sagar Gubbi Venkatesh, Nihesh Rathod, Shishir Kolathaya, Bharadwaj Amrutur

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

2012.01148 2021-01-05 cs.CY cs.AI cs.LG 62%

Applied Machine Learning for Games: A Graduate School Course

Yilei Zeng, Aayush Shah, Jameson Thai, Michael Zyda

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

Comments The Eleventh Symposium on Educational Advances in Artificial Intelligence (EAAI-21)

2012.10200 2020-12-21 cs.LG cs.AI cs.SY eess.SY stat.ML 62%

Exact Reduction of Huge Action Spaces in General Reinforcement Learning

Sultan Javed Majeed, Marcus Hutter

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

Comments A variant of this paper was presented at the AAAI-2021 proceedings

2008.05598 2020-12-03 cs.LG cs.AI 62%

Deep Model-Based Reinforcement Learning for High-Dimensional Problems, a Survey

Aske Plaat, Walter Kosters, Mike Preuss

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

2011.08728 2020-12-01 cs.RO cs.LG 62%

Fault-Aware Robust Control via Adversarial Reinforcement Learning

Fan Yang, Chao Yang, Di Guo, Huaping Liu, Fuchun Sun

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

Comments 7 pages, 7 figures

2011.13847 2020-11-30 cs.RO cs.LG 62%

Autonomous learning of multiple, context-dependent tasks

Vieri Giuliano Santucci, Davide Montella, Bruno Castro da Silva, Gianluca Baldassarre

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

2011.13467 2020-11-30 cs.AI cs.RO 62%

Episodic Self-Imitation Learning with Hindsight

Tianhong Dai, Hengyan Liu, Anil Anthony Bharath

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

1902.01670 2020-11-25 cs.LG cs.RO stat.ML 62%

Interactively shaping robot behaviour with unlabeled human instructions

Anis Najar, Olivier Sigaud, Mohamed Chetouani

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

Journal ref Auton Agent Multi-Agent Syst 34, 35 (2020)

2011.09586 2020-11-20 cs.RO cs.LG 62%

SAFARI: Safe and Active Robot Imitation Learning with Imagination

Norman Di Palo, Edward Johns

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

1805.09267 2020-11-19 cs.LG cs.AI stat.ML 62%

Reinforcement Learning for Heterogeneous Teams with PALO Bounds

Roi Ceren, Prashant Doshi, Keyang He

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

Journal ref Neurocomputing, Volume 420, 8 January 2021, Pages 36-56

1805.07871 2020-11-19 cs.LG cs.AI stat.ML 62%

A Framework and Method for Online Inverse Reinforcement Learning

Saurabh Arora, Prashant Doshi, Bikramjit Banerjee

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

Journal ref Journal of Autonomous Agents and Multi-Agent Systems, Volume 35, Article number: 4 (2021)

2011.08743 2020-11-18 cs.RO cs.AI cs.MA 62%

Curiosity Based Reinforcement Learning on Robot Manufacturing Cell

Mohammed Sharafath Abdul Hameed, Md Muzahid Khan, Andreas Schwung

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

Comments 6 pages

2011.06882 2020-11-16 eess.SY cs.LG cs.RO cs.SY 62%

Reinforcement Learning Control of Constrained Dynamic Systems with Uniformly Ultimate Boundedness Stability Guarantee

Minghao Han, Yuan Tian, Lixian Zhang, Jun Wang, Wei Pan

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

2011.04950 2020-11-11 cs.RO cs.AI cs.SY eess.SY 62%

Model-based Reinforcement Learning from Signal Temporal Logic Specifications

Parv Kapoor, Anand Balakrishnan, Jyotirmoy V. Deshmukh

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

Comments Submitted to ICRA 2021

2007.13134 2020-11-09 cs.RO cs.LG 62%

Data-efficient visuomotor policy training using reinforcement learning and generative models

Ali Ghadirzadeh, Petra Poklukar, Ville Kyrki, Danica Kragic, Mårten Björkman

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

2011.01298 2020-11-04 cs.RO cs.LG 62%

Shaping Rewards for Reinforcement Learning with Imperfect Demonstrations using Generative Models

Yuchen Wu, Melissa Mozifian, Florian Shkurti

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

Comments submitted to ICRA 2021

1. 模仿学习与强化学习 4115 篇

CLAMGen: Closed-Loop Arm Motion Generation via Multi-view Vision-Based RL

Near Optimal Policy Optimization via REPS

Baconian: A Unified Open-source Framework for Model-Based Reinforcement Learning

Zero-shot Policy Learning with Spatial Temporal RewardDecomposition on Contingency-aware Observation

Domain-Robust Visual Imitation Learning with Mutual Information Constraints

Continuous Transition: Improving Sample Efficiency for Continuous Control Problems via MixUp

The Sample Complexity of Teaching-by-Reinforcement on Q-Learning

Adversarial Environment Generation for Learning to Navigate the Web

How To Train Your HERON

Feedback in Imitation Learning: The Three Regimes of Covariate Shift

Improving Reinforcement Learning with Human Assistance: An Argument for Human Subject Studies with HIPPO Gym

Motion Generation Using Bilateral Control-Based Imitation Learning with Autoregressive Learning

Collision Avoidance in Pedestrian-Rich Environments with Deep Reinforcement Learning

CoachNet: An Adversarial Sampling Approach for Reinforcement Learning

Stochastic Action Prediction for Imitation Learning

Applied Machine Learning for Games: A Graduate School Course

Exact Reduction of Huge Action Spaces in General Reinforcement Learning

Deep Model-Based Reinforcement Learning for High-Dimensional Problems, a Survey

Fault-Aware Robust Control via Adversarial Reinforcement Learning

Autonomous learning of multiple, context-dependent tasks

Episodic Self-Imitation Learning with Hindsight

Interactively shaping robot behaviour with unlabeled human instructions

SAFARI: Safe and Active Robot Imitation Learning with Imagination

Reinforcement Learning for Heterogeneous Teams with PALO Bounds

A Framework and Method for Online Inverse Reinforcement Learning

Curiosity Based Reinforcement Learning on Robot Manufacturing Cell

Reinforcement Learning Control of Constrained Dynamic Systems with Uniformly Ultimate Boundedness Stability Guarantee

Model-based Reinforcement Learning from Signal Temporal Logic Specifications

Data-efficient visuomotor policy training using reinforcement learning and generative models

Shaping Rewards for Reinforcement Learning with Imperfect Demonstrations using Generative Models