Levine, Sergey

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

Eysenbach, B., Gupta, A., Ibarz, J., & Levine, S. (2018) · arXiv

Reinforcement Learning in RoboticsDomain Adaptation and Few-Shot Learning

Cited by 480

Model-Based Reinforcement Learning for Atari

Kaiser, L., Babaeizadeh, M., Milos, P., Osinski, B., Campbell, R. H., Czechowski, K., Erhan, D., Finn, C., Kozakowski, P., Levine, S., et al. (2019) · arXiv

Reinforcement Learning in RoboticsArtificial Intelligence in Games

Cited by 467

Learning deep control policies for autonomous aerial vehicles with MPC-guided policy search

Zhang, T., Kahn, G., Levine, S., & Abbeel, P. (2016) · 2016 IEEE International Conference on Robotics and Automation (ICRA)

Reinforcement Learning in RoboticsAdaptive Dynamic Programming Control

Cited by 452

Meta-World: A Benchmark and Evaluation for Multi-Task and Meta Reinforcement Learning

Yu, T., Quillen, D., He, Z., Julian, R., Narayan, A., Shively, H., Bellathur, A., Hausman, K., Finn, C., & Levine, S. (2019) · arXiv

Reinforcement Learning in RoboticsDomain Adaptation and Few-Shot Learning

Cited by 450

Data-efficient hierarchical reinforcement learning

Nachum, O., Gu, S., Lee, H., & Levine, S. (2018) · arXiv

Reinforcement Learning in RoboticsAI-based Problem Solving and Planning

Cited by 446

Learning to Walk Via Deep Reinforcement Learning

Haarnoja, T., Ha, S., Zhou, A., Tan, J., Tucker, G., & Levine, S. (2019) · Robotics: Science and Systems XV

Reinforcement Learning in RoboticsRobotic Locomotion and Control

Cited by 430

Sim-To-Real via Sim-To-Sim: Data-Efficient Robotic Grasping via Randomized-To-Canonical Adaptation Networks

James, S., Wohlhart, P., Kalakrishnan, M., Kalashnikov, D., Irpan, A., Ibarz, J., Levine, S., Hadsell, R., & Bousmalis, K. (2019) · 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Reinforcement Learning in RoboticsDomain Adaptation and Few-Shot Learning

Cited by 420

Learning to Adapt in Dynamic, Real-World Environments through Meta-Reinforcement Learning

Nagabandi, A., Clavera, I., Liu, S., Fearing, R. S., Abbeel, P., Levine, S., & Finn, C. (2018) · arXiv

Reinforcement Learning in RoboticsDomain Adaptation and Few-Shot Learning

Cited by 370

Reinforcement Learning and Control as Probabilistic Inference: Tutorial and Review

Levine, S. (2018) · arXiv

Reinforcement Learning in RoboticsAdaptive Dynamic Programming Control

Cited by 366

Learning Agile Robotic Locomotion Skills by Imitating Animals

Bin Peng, X., Coumans, E., Zhang, T., Lee, T.-W., Tan, J., & Levine, S. (2020) · Robotics: Science and Systems XVI

Robotic Locomotion and ControlReinforcement Learning in Robotics

Cited by 357

When to Trust Your Model: Model-Based Policy Optimization

Janner, M., Fu, J., Zhang, M., & Levine, S. (2019) · arXiv

Reinforcement Learning in RoboticsAdvanced Bandit Algorithms Research

Cited by 351

One-Shot Visual Imitation Learning via Meta-Learning

Finn, C., Yu, T., Zhang, T., Abbeel, P., & Levine, S. (2017) · arXiv

Reinforcement Learning in RoboticsRobot Manipulation and Learning

Cited by 341

Probabilistic Model-Agnostic Meta-Learning

Finn, C., Xu, K., & Levine, S. (2018) · arXiv

Domain Adaptation and Few-Shot LearningMachine Learning and Algorithms

Cited by 327

Self-Supervised Deep Reinforcement Learning with Generalized Computation Graphs for Robot Navigation

Kahn, G., Villaflor, A., Ding, B., Abbeel, P., & Levine, S. (2018) · 2018 IEEE International Conference on Robotics and Automation (ICRA)

Reinforcement Learning in RoboticsRobotics and Sensor-Based Localization

Cited by 308

π₀: A Vision-Language-Action Flow Model for General Robot Control

Black, K., Brown, N., Driess, D., Esmail, A., Equi, M., Finn, C., Fusai, N., Groom, L., Hausman, K., Ichter, B., et al. (2025) · Robotics: Science and Systems XXI

AI-based Problem Solving and PlanningRobot Manipulation and Learning

Cited by 295

Inner Monologue: Embodied Reasoning through Planning with Language Models

Huang, W., Xia, F., Xiao, T., Chan, H., Liang, J., Florence, P., Zeng, A., Tompson, J., Mordatch, I., Chebotar, Y., et al. (2022) · arXiv

AI-based Problem Solving and PlanningRobot Manipulation and Learning

Cited by 287

RT-2: Vision-Language-Action Models Transfer Web Knowledge to Robotic Control

Brohan, A., Brown, N., Carbajal, J., Chebotar, Y., Chen, X., Choromanski, K., Ding, T., Driess, D., Dubey, A., Finn, C., et al. (2023) · arXiv

Robot Manipulation and LearningMultimodal Machine Learning Applications

Cited by 276

Modular Multitask Reinforcement Learning with Policy Sketches

Andreas, J., Klein, D., & Levine, S. (2016) · arXiv

Reinforcement Learning in RoboticsDomain Adaptation and Few-Shot Learning

Cited by 274

Reinforcement Learning for Robust Parameterized Locomotion Control of Bipedal Robots

Li, Z., Cheng, X., Peng, X. B., Abbeel, P., Levine, S., Berseth, G., & Sreenath, K. (2021) · 2021 IEEE International Conference on Robotics and Automation (ICRA)

Robotic Locomotion and ControlReinforcement Learning in Robotics

Cited by 219

Open X-Embodiment: Robotic Learning Datasets and RT-X Models : Open X-Embodiment Collaboration 0

O’Neill, A., Rehman, A., Maddukuri, A., Gupta, A., Padalkar, A., Lee, A., Pooley, A., Gupta, A., Mandlekar, A., Jain, A., et al. (2024) · 2024 IEEE International Conference on Robotics and Automation (ICRA)

Robot Manipulation and LearningReinforcement Learning in Robotics

Cited by 210

Adversarial Policies: Attacking Deep Reinforcement Learning

Gleave, A., Dennis, M., Wild, C., Kant, N., Levine, S., & Russell, S. (2019) · arXiv

Adversarial Robustness in Machine LearningReinforcement Learning in Robotics

Cited by 200

MEMO: Test Time Robustness Via Adaptation and Augmentation

Zhang, M., Levine, S., & Finn, C. (2022) · Advances in Neural Information Processing Systems 35

Software Testing and Debugging TechniquesAdversarial Robustness in Machine Learning

Cited by 189

LM-Nav: Robotic Navigation with Large Pre-Trained Models of Language, Vision, and Action

Shah, D., Osinski, B., Ichter, B., & Levine, S. (2022) · arXiv

Reinforcement Learning in RoboticsRobot Manipulation and Learning

Cited by 179

AWAC: Accelerating Online Reinforcement Learning with Offline Datasets

Nair, A., Gupta, A., Dalal, M., & Levine, S. (2020) · arXiv

Reinforcement Learning in RoboticsRobot Manipulation and Learning

Cited by 175