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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 751–800 of 2122 papers

TitleStatusHype
Privileged to Predicted: Towards Sensorimotor Reinforcement Learning for Urban Driving—0
A Bayesian Approach to Robust Inverse Reinforcement LearningCode1
What Matters to Enhance Traffic Rule Compliance of Imitation Learning for End-to-End Autonomous Driving—0
Naturalistic Robot Arm Trajectory Generation via Representation Learning—0
Dissipative Imitation Learning for Discrete Dynamic Output Feedback Control with Sparse Data Sets—0
A Reinforcement Learning Approach for Robotic Unloading from Visual ObservationsCode0
Safe Neural Control for Non-Affine Control Systems with Differentiable Control Barrier Functions—0
Everyone Deserves A Reward: Learning Customized Human PreferencesCode1
REBOOT: Reuse Data for Bootstrapping Efficient Real-World Dexterous Manipulation—0
A Survey of Imitation Learning: Algorithms, Recent Developments, and Challenges—0
Self-driven Grounding: Large Language Model Agents with Automatical Language-aligned Skill Learning—0
Enhancing Robot Learning through Learned Human-Attention Feature MapsCode0
End-to-End Driving via Self-Supervised Imitation Learning Using Camera and LiDAR Data—0
BridgeData V2: A Dataset for Robot Learning at ScaleCode2
Conditional Kernel Imitation Learning for Continuous State Environments—0
Mimicking To Dominate: Imitation Learning Strategies for Success in Multiagent Competitive Games—0
ILCAS: Imitation Learning-Based Configuration-Adaptive Streaming for Live Video Analytics with Cross-Camera Collaboration—0
Preference-conditioned Pixel-based AI Agent For Game Testing—0
Small Object Detection via Coarse-to-fine Proposal Generation and Imitation LearningCode1
Regularizing Adversarial Imitation Learning Using Causal Invariance—0
IMM: An Imitative Reinforcement Learning Approach with Predictive Representation Learning for Automatic Market Making—0
Leveraging Symmetries in Pick and Place—0
Generating Personas for Games with Multimodal Adversarial Imitation Learning—0
Bootstrapping Developmental AIs: From Simple Competences to Intelligent Human-Compatible AIs—0
MOMA-Force: Visual-Force Imitation for Real-World Mobile Manipulation—0
Cognitive TransFuser: Semantics-guided Transformer-based Sensor Fusion for Improved Waypoint PredictionCode0
Initial State Interventions for Deconfounded Imitation Learning—0
Scaling Data Generation in Vision-and-Language NavigationCode2
Waypoint-Based Imitation Learning for Robotic Manipulation—0
Deep Homography Prediction for Endoscopic Camera Motion Imitation LearningCode0
Contextual Bandits and Imitation Learning via Preference-Based Active Queries—0
Offline Diversity Maximization Under Imitation Constraints—0
On Combining Expert Demonstrations in Imitation Learning via Optimal Transport—0
XSkill: Cross Embodiment Skill DiscoveryCode1
Multi-Stage Cable Routing through Hierarchical Imitation Learning—0
Scaling Laws for Imitation Learning in Single-Agent GamesCode1
Improving End-to-End Speech Translation by Imitation-Based Knowledge Distillation with Synthetic TranscriptsCode0
Selective Sampling and Imitation Learning via Online Regression—0
AnyTeleop: A General Vision-Based Dexterous Robot Arm-Hand Teleoperation System—0
Decomposing the Generalization Gap in Imitation Learning for Visual Robotic Manipulation—0
SpawnNet: Learning Generalizable Visuomotor Skills from Pre-trained Networks—0
Policy Contrastive Imitation Learning—0
Crossway Diffusion: Improving Diffusion-based Visuomotor Policy via Self-supervised LearningCode1
RH20T: A Comprehensive Robotic Dataset for Learning Diverse Skills in One-Shot—0
RObotic MAnipulation Network (ROMAN) x2013 Hybrid Hierarchical Learning for Solving Complex Sequential Tasks—0
Learning Dynamic Graph for Overtaking Strategy in Autonomous Driving—0
Learning non-Markovian Decision-Making from State-only SequencesCode0
IIFL: Implicit Interactive Fleet Learning from Heterogeneous Human SupervisorsCode0
On Imitation in Mean-field Games—0
CEIL: Generalized Contextual Imitation Learning—0
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