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Imitation Learning

Imitation Learning is a framework for learning a behavior policy from demonstrations. Usually, demonstrations are presented in the form of state-action trajectories, with each pair indicating the action to take at the state being visited. In order to learn the behavior policy, the demonstrated actions are usually utilized in two ways. The first, known as Behavior Cloning (BC), treats the action as the target label for each state, and then learns a generalized mapping from states to actions in a supervised manner. Another way, known as Inverse Reinforcement Learning (IRL), views the demonstrated actions as a sequence of decisions, and aims at finding a reward/cost function under which the demonstrated decisions are optimal.

Finally, a newer methodology, Inverse Q-Learning aims at directly learning Q-functions from expert data, implicitly representing rewards, under which the optimal policy can be given as a Boltzmann distribution similar to soft Q-learning

Source: Learning to Imitate

Papers

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Showing 451–500 of 2122 papers

TitleStatusHype
Learning Coordinated Bimanual Manipulation Policies using State Diffusion and Inverse Dynamics Models—0
Robust Offline Imitation Learning Through State-level Trajectory Stitching—0
Empirical Analysis of Sim-and-Real Cotraining Of Diffusion Policies For Planar Pushing from Pixels—0
Task Tokens: A Flexible Approach to Adapting Behavior Foundation Models—0
Neuro-Symbolic Imitation Learning: Discovering Symbolic Abstractions for Skill Learning—0
OminiAdapt: Learning Cross-Task Invariance for Robust and Environment-Aware Robotic Manipulation—0
Bridging the Sim-to-real Gap: A Control Framework for Imitation Learning of Model Predictive Control—0
Parental Guidance: Efficient Lifelong Learning through Evolutionary Distillation—0
End-to-end Sketch-Guided Path Planning through Imitation Learning for Autonomous Mobile RobotsCode0
BEAC: Imitating Complex Exploration and Task-oriented Behaviors for Invisible Object Nonprehensile Manipulation—0
TamedPUMA: safe and stable imitation learning with geometric fabrics—0
JARVIS-VLA: Post-Training Large-Scale Vision Language Models to Play Visual Games with Keyboards and Mouse—0
Denoising-based Contractive Imitation LearningCode0
Learning 3D Scene Analogies with Neural Contextual Scene Maps—0
RoboFactory: Exploring Embodied Agent Collaboration with Compositional Constraints—0
Robotic Paper Wrapping by Learning Force Control—0
StyleLoco: Generative Adversarial Distillation for Natural Humanoid Robot Locomotion—0
Online Imitation Learning for Manipulation via Decaying Relative Correction through Teleoperation—0
CCDP: Composition of Conditional Diffusion Policies with Guided Sampling—0
Learning Bimanual Manipulation via Action Chunking and Inter-Arm Coordination with Transformers—0
GR00T N1: An Open Foundation Model for Generalist Humanoid Robots—0
Quantization-Free Autoregressive Action TransformerCode0
HybridGen: VLM-Guided Hybrid Planning for Scalable Data Generation of Imitation Learning—0
FLEX: A Framework for Learning Robot-Agnostic Force-based Skills Involving Sustained Contact Object Manipulation—0
Efficient Imitation under Misspecification—0
GenOSIL: Generalized Optimal and Safe Robot Control using Parameter-Conditioned Imitation Learning—0
Residual Policy Gradient: A Reward View of KL-regularized Objective—0
Is Your Imitation Learning Policy Better than Mine? Policy Comparison with Near-Optimal Stopping—0
TASTE-Rob: Advancing Video Generation of Task-Oriented Hand-Object Interaction for Generalizable Robotic Manipulation—0
Sketch-to-Skill: Bootstrapping Robot Learning with Human Drawn Trajectory Sketches—0
From Abstraction to Reality: DARPA's Vision for Robust Sim-to-Real Autonomy—0
LUMOS: Language-Conditioned Imitation Learning with World Models—0
Spatial-Temporal Graph Diffusion Policy with Kinematic Modeling for Bimanual Robotic Manipulation—0
NIL: No-data Imitation Learning by Leveraging Pre-trained Video Diffusion Models—0
Finetuning Generative Trajectory Model with Reinforcement Learning from Human Feedback—0
Feasibility-aware Imitation Learning from Observations through a Hand-mounted Demonstration Interface—0
The Pitfalls of Imitation Learning when Actions are Continuous—0
SE(3)-Equivariant Robot Learning and Control: A Tutorial Survey—0
TLA: Tactile-Language-Action Model for Contact-Rich Manipulation—0
Imitation Learning of Correlated Policies in Stackelberg Games—0
One-Shot Dual-Arm Imitation Learning—0
Policy Regularization on Globally Accessible States in Cross-Dynamics Reinforcement Learning—0
How to Train Your Robots? The Impact of Demonstration Modality on Imitation Learning—0
A Simple Approach to Constraint-Aware Imitation Learning with Application to Autonomous RacingCode0
EPR-GAIL: An EPR-Enhanced Hierarchical Imitation Learning Framework to Simulate Complex User Consumption Behaviors—0
Learning to Drive by Imitating Surrounding Vehicles—0
Look Before You Leap: Using Serialized State Machine for Language Conditioned Robotic Manipulation—0
Kaiwu: A Multimodal Manipulation Dataset and Framework for Robot Learning and Human-Robot Interaction—0
dARt Vinci: Egocentric Data Collection for Surgical Robot Learning at Scale—0
Adapt3R: Adaptive 3D Scene Representation for Domain Transfer in Imitation Learning—0
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