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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 401–450 of 2122 papers

TitleStatusHype
Imitating Language via Scalable Inverse Reinforcement Learning—0
Preference-Based Multi-Agent Reinforcement Learning: Data Coverage and Algorithmic Techniques—0
MAPF-GPT: Imitation Learning for Multi-Agent Pathfinding at ScaleCode2
FlowRetrieval: Flow-Guided Data Retrieval for Few-Shot Imitation LearningCode0
Reinforcement Learning without Human Feedback for Last Mile Fine-Tuning of Large Language Models—0
Atari-GPT: Benchmarking Multimodal Large Language Models as Low-Level Policies in Atari Games—0
In-Context Imitation Learning via Next-Token PredictionCode2
Re-Mix: Optimizing Data Mixtures for Large Scale Imitation LearningCode1
Automating Deformable Gasket Assembly—0
Pareto Inverse Reinforcement Learning for Diverse Expert Policy Generation—0
ACE: A Cross-Platform Visual-Exoskeletons System for Low-Cost Dexterous Teleoperation—0
Optimizing Interpretable Decision Tree Policies for Reinforcement LearningCode0
A Survey of Embodied Learning for Object-Centric Robotic ManipulationCode3
RP1M: A Large-Scale Motion Dataset for Piano Playing with Bi-Manual Dexterous Robot Hands—0
Markov Balance Satisfaction Improves Performance in Strictly Batch Offline Imitation Learning—0
A Comparison of Imitation Learning Algorithms for Bimanual Manipulation—0
Personalized Dynamic Difficulty Adjustment -- Imitation Learning Meets Reinforcement LearningCode0
Semi-Supervised One-Shot Imitation Learning—0
Deep Generative Models in Robotics: A Survey on Learning from Multimodal Demonstrations—0
PLANRL: A Motion Planning and Imitation Learning Framework to Bootstrap Reinforcement Learning—0
Navigating the Human Maze: Real-Time Robot Pathfinding with Generative Imitation LearningCode0
Adversarial Safety-Critical Scenario Generation using Naturalistic Human Driving Priors—0
KOI: Accelerating Online Imitation Learning via Hybrid Key-state Guidance—0
CMR-Agent: Learning a Cross-Modal Agent for Iterative Image-to-Point Cloud Registration—0
ParkingE2E: Camera-based End-to-end Parking Network, from Images to PlanningCode4
Play to the Score: Stage-Guided Dynamic Multi-Sensory Fusion for Robotic Manipulation—0
VITAL: Interactive Few-Shot Imitation Learning via Visual Human-in-the-Loop Corrections—0
Evolution of cooperation in the public goods game with Q-learning—0
Imitation Learning for Intra-Day Power Grid Operation through Topology ActionsCode0
PP-TIL: Personalized Planning for Autonomous Driving with Instance-based Transfer Imitation LearningCode1
Recursive Introspection: Teaching Language Model Agents How to Self-Improve—0
PateGail: A Privacy-Preserving Mobility Trajectory Generator with Imitation LearningCode1
WayEx: Waypoint Exploration using a Single Demonstration—0
Offline Imitation Learning Through Graph Search and Retrieval—0
Is Behavior Cloning All You Need? Understanding Horizon in Imitation Learning—0
Thought-Like-Pro: Enhancing Reasoning of Large Language Models through Self-Driven Prolog-based Chain-of-Thought—0
The Art of Imitation: Learning Long-Horizon Manipulation Tasks from Few DemonstrationsCode1
R+X: Retrieval and Execution from Everyday Human Videos—0
Imitation learning with artificial neural networks for demand response with a heuristic control approach for heat pumpsCode0
Bellman Diffusion Models—0
A Graph-based Adversarial Imitation Learning Framework for Reliable & Realtime Fleet Scheduling in Urban Air Mobility—0
Exciting Action: Investigating Efficient Exploration for Learning Musculoskeletal Humanoid LocomotionCode1
DINO Pre-training for Vision-based End-to-end Autonomous Driving—0
Global Reinforcement Learning: Beyond Linear and Convex Rewards via Submodular Semi-gradient Methods—0
PAIL: Performance based Adversarial Imitation Learning Engine for Carbon Neutral Optimization—0
MetaUrban: An Embodied AI Simulation Platform for Urban Micromobility—0
Towards Human-Like Driving: Active Inference in Autonomous Vehicle Control—0
BiGym: A Demo-Driven Mobile Bi-Manual Manipulation BenchmarkCode3
Green Screen Augmentation Enables Scene Generalisation in Robotic ManipulationCode1
Explorative Imitation Learning: A Path Signature Approach for Continuous EnvironmentsCode1
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