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588 result(s) for “Continual Learning” Page 1 of 12
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A Framework for Neurosymbolic Goal-Conditioned Continual Learning for Open World Environments
Pierrick Lorang, Shivam Goel, Yash Shukla, Patrik Zips, Matthias Scheutz
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Continual Domain Randomization
Josip Josifovski, Sayantan Auddy, Mohammadhossein Malmir, Justus Piater, Alois Knoll, Nicolás Navarro-Guerrero
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Continual Learning for Autonomous Robots: A Prototype-Based Approach
Elvin Hajizada, Balachandran Swaminathan, Yulia Sandamirskaya
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Adaptive Robot Traversability Estimation Based on Self-Supervised Online Continual Learning in Unstructured Environments
Hyung-Suk Yoon, Ji-Hoon Hwang, Chan Kim, E-In Son, Se-Wook Yoo, Seung-Woo Seo
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Online Adaptation of Learned Vehicle Dynamics Model with Meta-Learning Approach
Yuki Tsuchiya, Thomas Balch, Paul Drews, Guy Rosman
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Experience-Learning Inspired Two-Step Reward Method for Efficient Legged Locomotion Learning towards Natural and Robust Gaits
Yinghui Li, Jinze Wu, Xin Liu, Weizhong Guo, Yufei Xue
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Neural ODE-Based Imitation Learning (NODE-IL): Data-Efficient Imitation Learning for Long-Horizon Multi-Skill Robot Manipulation
Shiyao Zhao, Yucheng Xu, Mohammadreza Kasaei, Mohsen Khadem, Zhibin (Alex) Li
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Safe CoR: A Dual-Expert Approach to Integrating Imitation Learning and Safe Reinforcement Learning Using Constraint Rewards
Hyeokjin Kwon, Gunmin Lee, Junseo Lee, Songhwai Oh
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StROL: Stabilized and Robust Online Learning from Humans
Shaunak Mehta, Forrest Meng, Andrea Bajcsy, Dylan Losey
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Learning When to Stop: Efficient Active Tactile Perception with Deep Reinforcement Learning
Christopher Niemann, David Philip Leins, Luca Lach, Robert Haschke
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Continuous Rapid Learning by Human Imitation Using Audio Prompts and One-Shot Learning
Jaime Duque Domingo, Miguel García-GÃ3mez, Eduardo Zalama, Jaime Gomez Garcia Bermejo
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Adaptive Curriculum Learning with Successor Features for Imbalanced Compositional Reward Functions
Laszlo Szoke, Shahaf Shperberg, Jarrett Holtz, Alessandro Gabriele Allievi
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Contact-Rich SE(3) Equivariant Robot Manipulation Task Learning Via Geometric Impedance Control
Joohwan Seo, Nikhil Potu Surya Prakash, Xiang Zhang, Changhao Wang, Jongeun Choi, Masayoshi Tomizuka, Roberto HOROWITZ
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Preventing Catastrophic Forgetting in Continuous Online Learning for Autonomous Driving
Rui Yang, Zhi Yan, Tao Yang, Tomáï¿1⁄2 Krajník, Yassine Ruichek
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Iterative Reference Learning for Cartesian Impedance Control of Robot Manipulators
Julian Mauricio Salt Ducaju, Bjorn Olofsson, Rolf Johansson
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Funnel-Based Reward Shaping for Signal Temporal Logic Tasks in Reinforcement Learning
Naman Saxena, Sandeep Gorantla, Pushpak Jagtap
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A Cascaded Broad Learning System for Manipulator Motion Control
Guoyu Zuo, Shuaifeng Dong, Jiyong Zhou, Shuangyue Yu
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Interactive Reinforcement Learning from Natural Language Feedback
Imene Tarakli, Samuele Vinanzi, Alessandro Di Nuovo
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Bi-CL: A Reinforcement Learning Framework for Robots Coordination through Bi-Level Optimization
Zechen Hu, Daigo Shishika, Xuesu Xiao, Xuan Wang
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Offline Meta-Reinforcement Learning with Evolving Gradient Agreement
Jiaxing Chen, Weilin Yuan, Shaofei Chen, furong liu, AO MA, Zhenzhen Hu, Peng Li
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Progressive Representation Learning for Real-Time UAV Tracking
Changhong Fu, Xiang Lei, Haobo Zuo, Liangliang Yao, Guangze Zheng, Jia Pan
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Crowd-Aware Robot Navigation with Switching between Learning-Based and Rule-Based Methods Using Normalizing Flows
Kohei Matsumoto, Yuki Hyodo, Ryo Kurazume
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MFC-EQ: Mean-Field Control with Envelope Q-Learning for Moving Decentralized Agents in Formation
Qiushi Lin, Hang Ma
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Tactile Active Inference Reinforcement Learning for Efficient Robotic Manipulation Skill Acquisition
Zihao Liu, Xing Liu, Zhengxiong Liu, Yizhai Zhang, Panfeng Huang
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Proto-CLIP: Vision-Language Prototypical Network for Few-Shot Learning
Jishnu Jaykumar P, Kamalesh Palanisamy, Yu-Wei Chao, Xinya Du, Yu Xiang
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MARRGM: Learning Framework for Multi-Agent Reinforcement Learning Via Reinforcement Recommendation and Group Modification
Wu, Peiliang,Tian, Liqiang,Zhang, Qian,Mao, BingYi,Chen, Wenbai
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Task and Domain Adaptive Reinforcement Learning for Robot Control
Yu Tang Liu, Nilaksh Nilaksh, Aamir Ahmad
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VoxelContrast: Voxel Contrast-Based Unsupervised Learning for 3D Point Clouds
Yuxiang Qin, HAO SUN
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A Safe Preference Learning Approach for Personalization with Applications to Autonomous Vehicles
Ruya Karagulle, Nikos Arechiga, Andrew Best, Jonathan DeCastro, Necmiye Ozay
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Learning-Informed Long-Horizon Navigation under Uncertainty for Vehicles with Dynamics
Abhish Khanal, Hoang-Dung Bui, Erion Plaku, Gregory Stein
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Constrained Bootstrapped Learning for Few-Shot Robot Skill Adaptation
A K M Nadimul Haque, Fouad Sukkar, Lukas Tanz, Marc Carmichael, Teresa A. Vidal-Calleja
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DRIFT: Deep Reinforcement Learning for Intelligent Floating Platforms Trajectories
Matteo El Hariry, Antoine Richard, Vivek Muralidharan, Matthieu Geist, Miguel A. Olivares-Mendez
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Learning Safe Locomotion for Quadrupedal Robots by Derived-Action Optimization
Deye Zhu, Chengrui Zhu, Zhen Zhang, Shuo Xin, Yong Liu
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Autonomous Landing on a Moving Platform Using Vision-Based Deep Reinforcement Learning
Pawel Ladosz, Meraj Mammadov, Heejung Shin, Woojae Shin, Hyondong Oh
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CaT: Constraints As Terminations for Legged Locomotion Reinforcement Learning
Elliot Chane-Sane, Pierre-Alexandre Leziart, Thomas Flayols, Olivier Stasse, Philippe Soueres, Nicolas Mansard
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Adaptive Social Force Window Planner with Reinforcement Learning
Mauro Martini, Noe Perez-Higueras, Andrea Ostuni, Marcello Chiaberge, Fernando Caballero, Luis Merino
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Learning Deep Dynamical Systems Using Stable Neural ODEs
Andreas Sochopoulos, Michael Gienger, Sethu Vijayakumar
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A Deep Reinforcement Learning Framework and Methodology for Reducing the Sim-to-Real Gap in ASV Navigation
Luis F. W. Batista, Junghwan Ro, Antoine Richard, Pete Schroepfer, Seth Hutchinson, Cedric Pradalier
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Fixing Symbolic Plans with Reinforcement Learning in Object-Based Action Spaces
Christopher Thierauf, Matthias Scheutz
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Communication-Efficient Multi-Robot Exploration Using Distributed Coverage-Biased Q-Learning
Ehsan Latif, Ramviyas Parasuraman
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RESPRECT: Speeding-Up Multi-Fingered Grasping with Residual Reinforcement Learning
Federico Ceola, Lorenzo Rosasco, Lorenzo Natale
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Active Learning for Forward/Inverse Kinematics of Redundantly-Driven Flexible Tensegrity Manipulator
Yuhei Yoshimitsu, Takayuki Osa, Heni Ben Amor, Shuhei Ikemoto
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Reinforcement Learning for Active Search and Grasp in Clutter
Thomas Pitcher, Julian Förster, Jen Jen Chung
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A Non-Homogeneity Mapless Navigation Based on Hierarchical Safe Reinforcement Learning in Dynamic Complex Environments
Jianmin Qin, Qingchen Liu, Qichao Ma, Zipeng Wu, Jiahu Qin
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Signal Temporal Logic-Guided Apprenticeship Learning
Aniruddh Gopinath Puranic, Jyotirmoy Deshmukh, Stefanos Nikolaidis
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SNF-Feat: Semantic-Guided Negative-Sample-Free Representation Learning for Local Feature Extraction
Xun Zhou, Qingqing Yan, Minghao Zhu, mengxian hu, Chengju Liu, Qijun Chen
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Hyperbolic Image-And-Pointcloud Contrastive Learning for 3D Classification
Naiwen Hu, Haozhe Cheng, Yifan Xie, Pengcheng Shi, Jihua Zhu
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Incremental Learning of Robotic Manipulation Tasks through Virtual Reality Demonstrations
Giuseppe Rauso, Riccardo Caccavale, Alberto Finzi
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Leveraging Demonstrator-Perceived Precision for Safe Interactive Imitation Learning of Clearance-Limited Tasks
Hanbit Oh, Takamitsu Matsubara
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CASRL: Collision Avoidance with Spiking Reinforcement Learning among Dynamic, Decision-Making Agents
Chengjun Zhang, Ka-Wa Yip, Bo Yang, Zhiyong Zhang, Mengwen Yuan, Rui Yan, Huajin Tang
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