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Reinforcement Learning
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Robotics
2069 directly classified papers
Papers per year
2005: 4
2006: 13
2007: 13
2008: 14
2009: 4
2010: 14
2011: 15
2012: 20
2013: 20
2014: 18
2015: 14
2016: 22
2017: 53
2018: 84
2019: 166
2020: 215
2021: 282
2022: 268
2023: 342
2024: 254
2025: 193
2026: 41
Papers
Learning Visually Guided Latent Actions for Assistive Teleoperation
L4DC 2021
Optimal Cost Design for Model Predictive Control
L4DC 2021
Episodic Learning for Safe Bipedal Locomotion with Control Barrier Functions and Projection-to-State Safety
L4DC 2021
RMP2: A Structured Composable Policy Class for Robot Learning
RSS 2021
Robust Multi-Modal Policies for Industrial Assembly via Reinforcement Learning and Demonstrations: A Large-Scale Study
RSS 2021
Tractable Reinforcement Learning of Signal Temporal Logic Objectives
L4DC 2020
Model-Based Reinforcement Learning with Value-Targeted Regression
L4DC 2020
Positive-Unlabeled Reward Learning
CORL 2020
Probably Approximately Correct Vision-Based Planning using Motion Primitives
CORL 2020
Exploratory Grasping: Asymptotically Optimal Algorithms for Grasping Challenging Polyhedral Objects
CORL 2020
Strategies for Cooperative UAVs Using Model Predictive Control
IJCAI 2020
Transparent Intent for Explainable Shared Control in Assistive Robotics
IJCAI 2020
Crowd-Steer: Realtime Smooth and Collision-Free Robot Navigation in Densely Crowded Scenarios Trained using High-Fidelity Simulation
IJCAI 2020
MULTIPOLAR: Multi-Source Policy Aggregation for Transfer Reinforcement Learning between Diverse Environmental Dynamics
IJCAI 2020
Semi-Markov Reinforcement Learning for Stochastic Resource Collection
IJCAI 2020
PackIt: A Virtual Environment for Geometric Planning
ICML 2020
Towards Autonomous Eye Surgery by Combining Deep Imitation Learning with Optimal Control
CORL 2020
Learning Robot Skills with Temporal Variational Inference
ICML 2020
Chaining Behaviors from Data with Model-Free Reinforcement Learning
CORL 2020
Explicitly Encouraging Low Fractional Dimensional Trajectories Via Reinforcement Learning
CORL 2020
Never Stop Learning: The Effectiveness of Fine-Tuning in Robotic Reinforcement Learning
CORL 2020
Tolerance-Guided Policy Learning for Adaptable and Transferrable Delicate Industrial Insertion
CORL 2020
Deep Reinforcement Learning with Population-Coded Spiking Neural Network for Continuous Control
CORL 2020
Visual Imitation Made Easy
CORL 2020
Deep Reactive Planning in Dynamic Environments
CORL 2020
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