Cover Image

On Feasible Rewards in Multi-Agent Inverse Reinforcement Learning

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Freihaut, Till, Ramponi, Giorgia
Format:	Preprint
Published:	2024
Subjects:	Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Learning Equilibria from Data: Provably Efficient Multi-Agent Imitation Learning
by: Freihaut, Till, et al.
Published: (2025)

Clustered KL-barycenter design for policy evaluation
by: Weissmann, Simon, et al.
Published: (2025)

Multi-agent imitation learning with function approximation: Linear Markov games and beyond
by: Viano, Luca, et al.
Published: (2026)

Rate optimal learning of equilibria from data
by: Freihaut, Till, et al.
Published: (2025)

Fine-tuning Behavioral Cloning Policies with Preference-Based Reinforcement Learning
by: Macuglia, Maël, et al.
Published: (2025)

Preference Elicitation for Offline Reinforcement Learning
by: Pace, Alizée, et al.
Published: (2024)

Exploiting Causal Graph Priors with Posterior Sampling for Reinforcement Learning
by: Mutti, Mirco, et al.
Published: (2023)

Contextual Bilevel Reinforcement Learning for Incentive Alignment
by: Thoma, Vinzenz, et al.
Published: (2024)

MAVRL: Learning Reward Functions from Multiple Feedback Types with Amortized Variational Inference
by: Baur, Raphaël, et al.
Published: (2026)

Inverse Reinforcement Learning without an Optimal Demonstrator: A Feasible Reward Set Approach
by: Kim, Kihyun, et al.
Published: (2026)

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

Truly No-Regret Learning in Constrained MDPs
by: Müller, Adrian, et al.
Published: (2024)

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

Multi-Agent Reinforcement Learning with Submodular Reward
by: Chen, Wenjing, et al.
Published: (2026)

Reward Design for Reinforcement Learning Agents
by: Devidze, Rati
Published: (2025)

Learning Acrobatic Flight from Preferences
by: Merk, Colin, et al.
Published: (2025)

Preference-Guided Learning for Sparse-Reward Multi-Agent Reinforcement Learning
by: Bui, The Viet, et al.
Published: (2025)

RDA: Reward Design Agent for Reinforcement Learning
by: Lee, Hojoon, et al.
Published: (2026)

On the Convergence of Single-Timescale Actor-Critic
by: Kumar, Navdeep, 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)

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

Multi-Agent Reinforcement Learning for Inverse Design in Photonic Integrated Circuits
by: Mahlau, Yannik, et al.
Published: (2025)

Multi-Agent Reinforcement Learning with a Hierarchy of Reward Machines
by: Zheng, Xuejing, et al.
Published: (2024)

Reward-Independent Messaging for Decentralized Multi-Agent Reinforcement Learning
by: Yoshida, Naoto, et al.
Published: (2025)

Redistributing Rewards Across Time and Agents for Multi-Agent Reinforcement Learning
by: Kapoor, Aditya, et al.
Published: (2025)

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

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

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

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

Inverse Feasibility in Over-the-Air Federated Learning
by: Piotrowski, Tomasz, et al.
Published: (2022)

Centralized Reward Agent for Knowledge Sharing and Transfer in Multi-Task Reinforcement Learning
by: Ma, Haozhe, et al.
Published: (2024)

Explicit Credit Assignment through Local Rewards and Dependence Graphs in Multi-Agent Reinforcement Learning
by: Le, Bang Giang, et al.
Published: (2026)

Spatiotemporal Attention-Augmented Inverse Reinforcement Learning for Multi-Agent Task Allocation
by: Yin, Huilin, et al.
Published: (2025)

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

Enhancing Inverse Reinforcement Learning through Encoding Dynamic Information in Reward Shaping
by: Zhan, Simon Sinong, et al.
Published: (2024)

Generalizing Behavior via Inverse Reinforcement Learning with Closed-Form Reward Centroids
by: Lazzati, Filippo, et al.
Published: (2025)

Inverse Reinforcement Learning with Switching Rewards and History Dependency for Characterizing Animal Behaviors
by: Ke, Jingyang, et al.
Published: (2025)

Learning Pareto-Optimal Rewards from Noisy Preferences: A Framework for Multi-Objective Inverse Reinforcement Learning
by: Cherukuri, Kalyan, et al.
Published: (2025)

Inverse Reinforcement Learning from Non-Stationary Learning Agents
by: Sivakumar, Kavinayan P., et al.
Published: (2024)

Rethinking Adversarial Inverse Reinforcement Learning: Policy Imitation, Transferable Reward Recovery and Algebraic Equilibrium Proof
by: Zhang, Yangchun, et al.
Published: (2024)