:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Zhang, Yangchun, Liu, Qiang, Li, Weiming, Zhou, Yirui
Format:	Preprint
Published:	2024
Subjects:	Machine Learning
Online Access:	https://arxiv.org/abs/2403.14593
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

On Reward Transferability in Adversarial Inverse Reinforcement Learning: Insights from Random Matrix Theory
by: Zhang, Yangchun, et al.
Published: (2024)

PAGAR: Taming Reward Misalignment in Inverse Reinforcement Learning-Based Imitation Learning with Protagonist Antagonist Guided Adversarial Reward
by: Zhou, Weichao, et al.
Published: (2023)

On Generalization and Distributional Update for Mimicking Observations with Adequate Exploration
by: Zhou, Yirui, et al.
Published: (2025)

Diffusion-Reward Adversarial Imitation Learning
by: Lai, Chun-Mao, et al.
Published: (2024)

Learning Rewards, Not Labels: Adversarial Inverse Reinforcement Learning for Machinery Fault Detection
by: Neupane, Dhiraj, et al.
Published: (2026)

Reward Transfer from Inverse Reinforcement Learning: A Coupled Minimax Approach
by: Hao, Guang-Yuan, et al.
Published: (2026)

Towards the Transferability of Rewards Recovered via Regularized Inverse Reinforcement Learning
by: Schlaginhaufen, Andreas, et al.
Published: (2024)

Rethinking Adversarial Attacks in Reinforcement Learning from Policy Distribution Perspective
by: Duan, Tianyang, et al.
Published: (2025)

Rethinking Inverse Reinforcement Learning: from Data Alignment to Task Alignment
by: Zhou, Weichao, et al.
Published: (2024)

Adversarial Inverse Reinforcement Learning for Mean Field Games
by: Chen, Yang, et al.
Published: (2021)

Inverse Reinforcement Learning With Constraint Recovery
by: Das, Nirjhar, et al.
Published: (2023)

Structured Imitation Learning of Interactive Policies through Inverse Games
by: Sun, Max M., et al.
Published: (2025)

Blending Imitation and Reinforcement Learning for Robust Policy Improvement
by: Liu, Xuefeng, et al.
Published: (2023)

From Novelty to Imitation: Self-Distilled Rewards for Offline Reinforcement Learning
by: Chaudhary, Gaurav, et al.
Published: (2025)

Imitating Language via Scalable Inverse Reinforcement Learning
by: Wulfmeier, Markus, et al.
Published: (2024)

Auto-Encoding Adversarial Imitation Learning
by: Zhang, Kaifeng, et al.
Published: (2022)

AdaFlow: Imitation Learning with Variance-Adaptive Flow-Based Policies
by: Hu, Xixi, et al.
Published: (2024)

Near-Optimal Second-Order Guarantees for Model-Based Adversarial Imitation Learning
by: Li, Shangzhe, et al.
Published: (2025)

Inverse Contextual Bandits without Rewards: Learning from a Non-Stationary Learner via Suffix Imitation
by: Kong, Yuqi, et al.
Published: (2026)

On Feasible Rewards in Multi-Agent Inverse Reinforcement Learning
by: Freihaut, Till, et al.
Published: (2024)

Bayesian Inverse Reinforcement Learning for Non-Markovian Rewards
by: Topper, Noah, et al.
Published: (2024)

Provably Efficient Off-Policy Adversarial Imitation Learning with Convergence Guarantees
by: Chen, Yilei, et al.
Published: (2024)

Diverse Policies Recovering via Pointwise Mutual Information Weighted Imitation Learning
by: Yang, Hanlin, et al.
Published: (2024)

Off-Dynamics Reinforcement Learning via Domain Adaptation and Reward Augmented Imitation
by: Guo, Yihong, et al.
Published: (2024)

Multi-Objective and Mixed-Reward Reinforcement Learning via Reward-Decorrelated Policy Optimization
by: Bai, Yang, et al.
Published: (2026)

Enhancing Security in Deep Reinforcement Learning: A Comprehensive Survey on Adversarial Attacks and Defenses
by: Yichao, Wu, et al.
Published: (2025)

Multi Task Inverse Reinforcement Learning for Common Sense Reward
by: Glazer, Neta, et al.
Published: (2024)

Reward-free World Models for Online Imitation Learning
by: Li, Shangzhe, et al.
Published: (2024)

Reinforcement Learning from Bagged Reward
by: Tang, Yuting, et al.
Published: (2024)

Contractive Dynamical Imitation Policies for Efficient Out-of-Sample Recovery
by: Abyaneh, Amin, et al.
Published: (2024)

Contextualized Policy Recovery: Modeling and Interpreting Medical Decisions with Adaptive Imitation Learning
by: Deuschel, Jannik, et al.
Published: (2023)

Beyond Binary: Turning Partial Success into Dense Verifiable Rewards for Reinforcement Learning in Code Generation
by: Wang, Longwen, et al.
Published: (2026)

Focal Reward: Balanced Reinforcement Learning under Rubric-Based Rewards
by: Huang, Yu, et al.
Published: (2026)

Inverse Reinforcement Learning with Dynamic Reward Scaling for LLM Alignment
by: Cheng, Ruoxi, et al.
Published: (2025)

Stealthy Imitation: Reward-guided Environment-free Policy Stealing
by: Zhuang, Zhixiong, et al.
Published: (2024)

SD2AIL: Adversarial Imitation Learning from Synthetic Demonstrations via Diffusion Models
by: Li, Pengcheng, et al.
Published: (2025)

Latent Wasserstein Adversarial Imitation Learning
by: Yang, Siqi, et al.
Published: (2026)

Your Self-Play Algorithm is Secretly an Adversarial Imitator: Understanding LLM Self-Play through the Lens of Imitation Learning
by: Li, Shangzhe, et al.
Published: (2026)

TW-CRL: Time-Weighted Contrastive Reward Learning for Efficient Inverse Reinforcement Learning
by: Li, Yuxuan, et al.
Published: (2025)

Expert Proximity as Surrogate Rewards for Single Demonstration Imitation Learning
by: Chiang, Chia-Cheng, et al.
Published: (2024)