机器人 / 具身智能 - arXivDaily 专题

2202.09514 2022-09-27 cs.LG cs.AI cs.GT 62%

Robust Reinforcement Learning as a Stackelberg Game via Adaptively-Regularized Adversarial Training

Peide Huang, Mengdi Xu, Fei Fang, Ding Zhao

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

2106.08746 2022-09-26 cs.LG cs.AI cs.CR 62%

Real-time Adversarial Perturbations against Deep Reinforcement Learning Policies: Attacks and Defenses

Buse G. A. Tekgul, Shelly Wang, Samuel Marchal, N. Asokan

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

Comments Will appear in the proceedings of ESORICS 2022; 13 pages, 6 figures, 6 tables

2209.09536 2022-09-21 cs.LG cs.AI 62%

Towards Task-Prioritized Policy Composition

Finn Rietz, Erik Schaffernicht, Todor Stoyanov, Johannes A. Stork

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

2209.07996 2022-09-19 cs.RO cs.AI 62%

SoLo T-DIRL: Socially-Aware Dynamic Local Planner based on Trajectory-Ranked Deep Inverse Reinforcement Learning

Yifan Xu, Theodor Chakhachiro, Tribhi Kathuria, Maani Ghaffari

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

2209.03800 2022-09-13 cs.RO cs.AI 62%

Double Q-Learning for Citizen Relocation During Natural Hazards

Alysson Ribeiro da Silva

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

Comments Technical Report on Double Q-Learning for Citizen Relocation During Natural Hazards

2209.03859 2022-09-09 cs.MA cs.AI cs.LG 62%

A Survey on Large-Population Systems and Scalable Multi-Agent Reinforcement Learning

Kai Cui, Anam Tahir, Gizem Ekinci, Ahmed Elshamanhory, Yannick Eich, Mengguang Li, Heinz Koeppl

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

2207.09372 2022-09-09 cs.RO cs.AI 62%

On Decentralizing Federated Reinforcement Learning in Multi-Robot Scenarios

Jayprakash S. Nair, Divya D. Kulkarni, Ajitem Joshi, Sruthy Suresh

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

Comments Submitted to SEEDA 2022. This arxiv is a preprint and NOT the final version

2209.02954 2022-09-08 cs.RO cs.AI 62%

A Deep Reinforcement Learning Strategy for UAV Autonomous Landing on a Platform

Z. Jiang, G. Song

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

2208.04822 2022-08-31 cs.LG cs.AI 62%

Generalized Reinforcement Learning: Experience Particles, Action Operator, Reinforcement Field, Memory Association, and Decision Concepts

Po-Hsiang Chiu, Manfred Huber

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

Comments 37 pages, 15 figures

2109.02791 2022-08-29 cs.RO cs.FL cs.LG 62%

Safety-Critical Learning of Robot Control with Temporal Logic Specifications

Mingyu Cai, Cristian-Ioan Vasile

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

Comments Under Review. arXiv admin note: text overlap with arXiv:2102.12855

2105.14363 2022-08-23 cs.LG cs.AI stat.ML 62%

On the Theory of Reinforcement Learning with Once-per-Episode Feedback

Niladri S. Chatterji, Aldo Pacchiano, Peter L. Bartlett, Michael I. Jordan

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

Comments Published at NeurIPS 2022

2109.11978 2022-08-22 cs.RO cs.LG 62%

Learning to Walk in Minutes Using Massively Parallel Deep Reinforcement Learning

Nikita Rudin, David Hoeller, Philipp Reist, Marco Hutter

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

Comments CoRL 2021 Project website: : https://leggedrobotics.github.io/legged_gym/ Video: https://youtu.be/8sO7VS3q8d0

2104.00385 2022-08-09 cs.LG cs.RO 62%

Optimization Algorithm for Feedback and Feedforward Policies towards Robot Control Robust to Sensing Failures

Taisuke Kobayashi, Kenta Yoshizawa

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

Comments 23 pages, 12 figures

Journal ref ROBOMECH Journal, 2022

2102.00168 2022-08-09 cs.AI cs.RO 62%

Learning Skills to Navigate without a Master: A Sequential Multi-Policy Reinforcement Learning Algorithm

Ambedkar Dukkipati, Rajarshi Banerjee, Ranga Shaarad Ayyagari, Dhaval Parmar Udaybhai

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

Comments IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS): 2022

2208.02434 2022-08-05 cs.LG cs.RO 62%

Backward Imitation and Forward Reinforcement Learning via Bi-directional Model Rollouts

Yuxin Pan, Fangzhen Lin

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

Comments Accepted by IROS2022

2207.14140 2022-07-29 cs.LG cs.AI 62%

Playing a 2D Game Indefinitely using NEAT and Reinforcement Learning

Jerin Paul Selvan, Pravin S. Game

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

Comments 5 pages, 7 figures, 3 tables

2202.00850 2022-07-26 cs.CV cs.LG cs.SD eess.AS eess.IV 62%

Active Audio-Visual Separation of Dynamic Sound Sources

Sagnik Majumder, Kristen Grauman

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

Comments Accepted to ECCV 2022

2203.10519 2022-07-20 cs.RO cs.LG cs.NE 62%

Reinforcement learning reward function in unmanned aerial vehicle control tasks

Mikhail S. Tovarnov, Nikita V. Bykov

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

Journal ref J. Phys.: Conf. Ser. 2308 012004 (2022)

2207.02007 2022-07-08 cs.LG cs.AI 62%

The StarCraft Multi-Agent Challenges+ : Learning of Multi-Stage Tasks and Environmental Factors without Precise Reward Functions

Mingyu Kim, Jihwan Oh, Yongsik Lee, Joonkee Kim, Seonghwan Kim, Song Chong, Se-Young Yun

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

Comments ICML Workshop: AI for Agent Based Modeling 2022 Spotlight

2207.00978 2022-07-05 cs.LG cs.RO 62%

Renaissance Robot: Optimal Transport Policy Fusion for Learning Diverse Skills

Julia Tan, Ransalu Senanayake, Fabio Ramos

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

2109.15233 2022-06-29 cs.RO cs.LG 62%

Solving the Real Robot Challenge using Deep Reinforcement Learning

Robert McCarthy, Francisco Roldan Sanchez, Qiang Wang, David Cordova Bulens, Kevin McGuinness, Noel O'Connor, Stephen J. Redmond

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

Comments Published in AICS 2021 (http://ceur-ws.org/Vol-3105/paper41.pdf). Paper updated to clarify procedure used to train the policy

2206.12030 2022-06-27 cs.LG cs.AI 62%

Phasic Self-Imitative Reduction for Sparse-Reward Goal-Conditioned Reinforcement Learning

Yunfei Li, Tian Gao, Jiaqi Yang, Huazhe Xu, Yi Wu

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

Comments Accepted at ICML 2022

2206.11795 2022-06-24 cs.LG cs.AI 62%

Video PreTraining (VPT): Learning to Act by Watching Unlabeled Online Videos

Bowen Baker, Ilge Akkaya, Peter Zhokhov, Joost Huizinga, Jie Tang, Adrien Ecoffet, Brandon Houghton, Raul Sampedro, Jeff Clune

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

2206.11299 2022-06-24 cs.LG cs.RO 62%

Latent Policies for Adversarial Imitation Learning

Tianyu Wang, Nikhil Karnwal, Nikolay Atanasov

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

Comments 8 pages, 5 figures

2206.03654 2022-06-09 cs.NE cs.AI cs.LG 62%

Solving the Spike Feature Information Vanishing Problem in Spiking Deep Q Network with Potential Based Normalization

Yinqian Sun, Yi Zeng, Yang Li

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

2206.03312 2022-06-08 cs.NE cs.AI cs.LG 62%

Neuro-Nav: A Library for Neurally-Plausible Reinforcement Learning

Arthur Juliani, Samuel Barnett, Brandon Davis, Margaret Sereno, Ida Momennejad

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

2110.04156 2022-06-07 cs.LG cs.AI 62%

Showing Your Offline Reinforcement Learning Work: Online Evaluation Budget Matters

Vladislav Kurenkov, Sergey Kolesnikov

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

Comments ICML 2022, Spotlight; https://tinkoff-ai.github.io/eop/

2206.00142 2022-06-02 cs.LG cs.AI cs.CL 62%

IGLU Gridworld: Simple and Fast Environment for Embodied Dialog Agents

Artem Zholus, Alexey Skrynnik, Shrestha Mohanty, Zoya Volovikova, Julia Kiseleva, Artur Szlam, Marc-Alexandre Coté, Aleksandr I. Panov

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

2205.15023 2022-05-31 cs.LG cs.AI 62%

Scalable Multi-Agent Model-Based Reinforcement Learning

Vladimir Egorov, Aleksei Shpilman

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

Comments AAMAS'2022, cite https://dl.acm.org/doi/abs/10.5555/3535850.3535894

2205.12401 2022-05-26 cs.LG cs.AI 62%

Reward Uncertainty for Exploration in Preference-based Reinforcement Learning

Xinran Liang, Katherine Shu, Kimin Lee, Pieter Abbeel

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

Comments ICLR 2022. Last two authors advised equally

1. 模仿学习与强化学习 4115 篇

Robust Reinforcement Learning as a Stackelberg Game via Adaptively-Regularized Adversarial Training

Real-time Adversarial Perturbations against Deep Reinforcement Learning Policies: Attacks and Defenses

Towards Task-Prioritized Policy Composition

SoLo T-DIRL: Socially-Aware Dynamic Local Planner based on Trajectory-Ranked Deep Inverse Reinforcement Learning

Double Q-Learning for Citizen Relocation During Natural Hazards

A Survey on Large-Population Systems and Scalable Multi-Agent Reinforcement Learning

On Decentralizing Federated Reinforcement Learning in Multi-Robot Scenarios

A Deep Reinforcement Learning Strategy for UAV Autonomous Landing on a Platform

Generalized Reinforcement Learning: Experience Particles, Action Operator, Reinforcement Field, Memory Association, and Decision Concepts

Safety-Critical Learning of Robot Control with Temporal Logic Specifications

On the Theory of Reinforcement Learning with Once-per-Episode Feedback

Learning to Walk in Minutes Using Massively Parallel Deep Reinforcement Learning

Optimization Algorithm for Feedback and Feedforward Policies towards Robot Control Robust to Sensing Failures

Learning Skills to Navigate without a Master: A Sequential Multi-Policy Reinforcement Learning Algorithm

Backward Imitation and Forward Reinforcement Learning via Bi-directional Model Rollouts

Playing a 2D Game Indefinitely using NEAT and Reinforcement Learning

Active Audio-Visual Separation of Dynamic Sound Sources

Reinforcement learning reward function in unmanned aerial vehicle control tasks

The StarCraft Multi-Agent Challenges+ : Learning of Multi-Stage Tasks and Environmental Factors without Precise Reward Functions

Renaissance Robot: Optimal Transport Policy Fusion for Learning Diverse Skills

Solving the Real Robot Challenge using Deep Reinforcement Learning

Phasic Self-Imitative Reduction for Sparse-Reward Goal-Conditioned Reinforcement Learning

Video PreTraining (VPT): Learning to Act by Watching Unlabeled Online Videos

Latent Policies for Adversarial Imitation Learning

Solving the Spike Feature Information Vanishing Problem in Spiking Deep Q Network with Potential Based Normalization

Neuro-Nav: A Library for Neurally-Plausible Reinforcement Learning

Showing Your Offline Reinforcement Learning Work: Online Evaluation Budget Matters

IGLU Gridworld: Simple and Fast Environment for Embodied Dialog Agents

Scalable Multi-Agent Model-Based Reinforcement Learning

Reward Uncertainty for Exploration in Preference-based Reinforcement Learning