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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 801–850 of 2122 papers

TitleStatusHype
ILAEDA: An Imitation Learning Based Approach for Automatic Exploratory Data Analysis—0
BC-Z: Zero-Shot Task Generalization with Robotic Imitation Learning—0
Task-Agnostic Learning to Accomplish New Tasks—0
IDIL: Imitation Learning of Intent-Driven Expert Behavior—0
Identifying Selections for Unsupervised Subtask Discovery—0
Identifying Differential Patient Care Through Inverse Intent Inference—0
IBCB: Efficient Inverse Batched Contextual Bandit for Behavioral Evolution History—0
I2D2: Inductive Knowledge Distillation with NeuroLogic and Self-Imitation—0
Deep Generative Models in Robotics: A Survey on Learning from Multimodal Demonstrations—0
Adapt3R: Adaptive 3D Scene Representation for Domain Transfer in Imitation Learning—0
Accelerating Training in Pommerman with Imitation and Reinforcement Learning—0
Towards Biosignals-Free Autonomous Prosthetic Hand Control via Imitation Learning—0
Deep Bayesian Reward Learning from Preferences—0
Bayesian Multi-type Mean Field Multi-agent Imitation Learning—0
Hybrid Imitation Learning for Real-Time Service Restoration in Resilient Distribution Systems—0
Hybrid Adversarial Imitation Learning—0
Decoupling Skill Learning from Robotic Control for Generalizable Object Manipulation—0
Bayesian Learning for Dynamic Inference—0
A Linearly Constrained Nonparametric Framework for Imitation Learning—0
Human-Robot Navigation using Event-based Cameras and Reinforcement Learning—0
Human-like Bots for Tactical Shooters Using Compute-Efficient Sensors—0
Human-in-the-Loop Task and Motion Planning for Imitation Learning—0
Human-in-the-Loop Imitation Learning using Remote Teleoperation—0
HybridGen: VLM-Guided Hybrid Planning for Scalable Data Generation of Imitation Learning—0
Decomposing the Generalization Gap in Imitation Learning for Visual Robotic Manipulation—0
Hybrid Imitation-Learning Motion Planner for Urban Driving—0
Bayesian Imitation Learning for End-to-End Mobile Manipulation—0
Human AI interaction loop training: New approach for interactive reinforcement learning—0
Human-Agent Cooperation in Bridge Bidding—0
Hyperparameter Selection for Imitation Learning—0
Human2LocoMan: Learning Versatile Quadrupedal Manipulation with Human Pretraining—0
Synthesizing Decentralized Controllers with Graph Neural Networks and Imitation Learning—0
Batch Recurrent Q-Learning for Backchannel Generation Towards Engaging Agents—0
Align Your Intents: Offline Imitation Learning via Optimal Transport—0
AdaManip: Adaptive Articulated Object Manipulation Environments and Policy Learning—0
How to Train Your Robots? The Impact of Demonstration Modality on Imitation Learning—0
How To Not Train Your Dragon: Training-free Embodied Object Goal Navigation with Semantic Frontiers—0
DEALIO: Data-Efficient Adversarial Learning for Imitation from Observation—0
DDIL: Diversity Enhancing Diffusion Distillation With Imitation Learning—0
How hard is it to cross the room? -- Training (Recurrent) Neural Networks to steer a UAV—0
How Do We Move: Modeling Human Movement with System Dynamics—0
HOMIE: Humanoid Loco-Manipulation with Isomorphic Exoskeleton Cockpit—0
ILCAS: Imitation Learning-Based Configuration-Adaptive Streaming for Live Video Analytics with Cross-Camera Collaboration—0
IL-flOw: Imitation Learning from Observation using Normalizing Flows—0
D-CODA: Diffusion for Coordinated Dual-Arm Data Augmentation—0
Data Quality in Imitation Learning—0
Hindsight is Only 50/50: Unsuitability of MDP based Approximate POMDP Solvers for Multi-resolution Information Gathering—0
Imitate TheWorld: A Search Engine Simulation Platform—0
Hindsight Generative Adversarial Imitation Learning—0
DataMIL: Selecting Data for Robot Imitation Learning with Datamodels—0
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