SOTAVerified

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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 301–350 of 2122 papers

TitleStatusHype
CALVIN: A Benchmark for Language-Conditioned Policy Learning for Long-Horizon Robot Manipulation TasksCode1
DiffTORI: Differentiable Trajectory Optimization for Deep Reinforcement and Imitation LearningCode1
A Bayesian Approach to Robust Inverse Reinforcement LearningCode1
CLIPort: What and Where Pathways for Robotic ManipulationCode1
DotaMath: Decomposition of Thought with Code Assistance and Self-correction for Mathematical ReasoningCode1
Dual RL: Unification and New Methods for Reinforcement and Imitation LearningCode1
Imitation Learning via Differentiable PhysicsCode1
Imitation Learning via Off-Policy Distribution MatchingCode1
DERAIL: Diagnostic Environments for Reward And Imitation LearningCode1
Improving Code Generation by Training with Natural Language FeedbackCode1
DEMO: Reframing Dialogue Interaction with Fine-grained Element ModelingCode1
Inverse Reinforcement Learning without Reinforcement LearningCode1
DexMV: Imitation Learning for Dexterous Manipulation from Human VideosCode1
CAFE-AD: Cross-Scenario Adaptive Feature Enhancement for Trajectory Planning in Autonomous DrivingCode1
CACTI: A Framework for Scalable Multi-Task Multi-Scene Visual Imitation LearningCode1
LaND: Learning to Navigate from DisengagementsCode1
DeformPAM: Data-Efficient Learning for Long-horizon Deformable Object Manipulation via Preference-based Action AlignmentCode1
Language-Conditioned Imitation Learning for Robot Manipulation TasksCode1
When should we prefer Decision Transformers for Offline Reinforcement Learning?Code1
Learning from Guided Play: A Scheduled Hierarchical Approach for Improving Exploration in Adversarial Imitation LearningCode1
Learning Large Neighborhood Search for Vehicle Routing in Airport Ground HandlingCode1
Deep Imitation Learning for Bimanual Robotic ManipulationCode1
CRIL: Continual Robot Imitation Learning via Generative and Prediction ModelCode1
Learning to combine primitive skills: A step towards versatile robotic manipulationCode1
Combining Learning from Human Feedback and Knowledge Engineering to Solve Hierarchical Tasks in MinecraftCode1
Learning Structural Edits via Incremental Tree TransformationsCode1
A deep inverse reinforcement learning approach to route choice modeling with context-dependent rewardsCode1
Critic Guided Segmentation of Rewarding Objects in First-Person ViewsCode1
LeTFuser: Light-weight End-to-end Transformer-Based Sensor Fusion for Autonomous Driving with Multi-Task LearningCode1
LeTO: Learning Constrained Visuomotor Policy with Differentiable Trajectory OptimizationCode1
Adversarial Option-Aware Hierarchical Imitation LearningCode1
LIV: Language-Image Representations and Rewards for Robotic ControlCode1
Curriculum Offline Imitation LearningCode1
Augmenting GAIL with BC for sample efficient imitation learningCode1
DeFIX: Detecting and Fixing Failure Scenarios with Reinforcement Learning in Imitation Learning Based Autonomous DrivingCode1
Dynamic Conditional Imitation Learning for Autonomous DrivingCode1
A System for Morphology-Task Generalization via Unified Representation and Behavior DistillationCode1
Learning Exploration Policies for NavigationCode1
Active Imitation Learning with Noisy GuidanceCode1
Mitigating Covariate Shift in Imitation Learning via Offline Data Without Great CoverageCode1
Atari-HEAD: Atari Human Eye-Tracking and Demonstration DatasetCode1
Bridging the Sim-to-real Gap: A Control Framework for Imitation Learning of Model Predictive Control—0
Bridging the Resource Gap: Deploying Advanced Imitation Learning Models onto Affordable Embedded Platforms—0
An Imitation Learning Curriculum for Text Editing with Non-Autoregressive Models—0
Bridging the Imitation Gap by Adaptive Insubordination—0
An Imitation Learning Based Algorithm Enabling Priori Knowledge Transfer in Modern Electricity Markets for Bayesian Nash Equilibrium Estimation—0
Bridging the Communication Gap: Artificial Agents Learning Sign Language through Imitation—0
Bridging Offline Reinforcement Learning and Imitation Learning: A Tale of Pessimism—0
An Imitation Learning Approach for Cache Replacement—0
Bridging Imitation and Online Reinforcement Learning: An Optimistic Tale—0
Show:102550
← PrevPage 7 of 43Next →

No leaderboard results yet.