Cover Image

MABL: Bi-Level Latent-Variable World Model for Sample-Efficient Multi-Agent Reinforcement Learning

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Venugopal, Aravind, Milani, Stephanie, Fang, Fei, Ravindran, Balaraman
Format:	Preprint
Published:	2023
Subjects:	Machine Learning Multiagent Systems
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Making Teams and Influencing Agents: Efficiently Coordinating Decision Trees for Interpretable Multi-Agent Reinforcement Learning
by: Chen, Rex, et al.
Published: (2025)

Transformer World Model for Sample Efficient Multi-Agent Reinforcement Learning
by: Deihim, Azad, et al.
Published: (2025)

Multi-Agent Reinforcement Learning for Sample-Efficient Deep Neural Network Mapping
by: Krishnan, Srivatsan, et al.
Published: (2025)

Sample-Efficient Robust Multi-Agent Reinforcement Learning in the Face of Environmental Uncertainty
by: Shi, Laixi, et al.
Published: (2024)

Sample-Efficient Distributionally Robust Multi-Agent Reinforcement Learning via Online Interaction
by: Farhat, Zain Ulabedeen, et al.
Published: (2025)

Inferring Latent Temporal Sparse Coordination Graph for Multi-Agent Reinforcement Learning
by: Duan, Wei, et al.
Published: (2024)

MARVEL: Multi-Agent Reinforcement-Learning for Large-Scale Variable Speed Limits
by: Zhang, Yuhang, et al.
Published: (2023)

Higher Replay Ratio Empowers Sample-Efficient Multi-Agent Reinforcement Learning
by: Xu, Linjie, et al.
Published: (2024)

Provably Efficient Information-Directed Sampling Algorithms for Multi-Agent Reinforcement Learning
by: Zhang, Qiaosheng, et al.
Published: (2024)

Towards Better Sample Efficiency in Multi-Agent Reinforcement Learning via Exploration
by: Baghi, Amir, et al.
Published: (2025)

Decentralized Transformers with Centralized Aggregation are Sample-Efficient Multi-Agent World Models
by: Zhang, Yang, et al.
Published: (2024)

Sample-Efficient Hypergradient Estimation for Decentralized Bi-Level Reinforcement Learning
by: Kudo, Mikoto, et al.
Published: (2026)

Ensemble Value Functions for Efficient Exploration in Multi-Agent Reinforcement Learning
by: Schäfer, Lukas, et al.
Published: (2023)

Efficient Episodic Memory Utilization of Cooperative Multi-Agent Reinforcement Learning
by: Na, Hyungho, et al.
Published: (2024)

Generalized Intention Modeling in Multi-Agent Reinforcement Learning
by: Odrowaz-Sypniewski, Mateusz, et al.
Published: (2026)

SigmaRL: A Sample-Efficient and Generalizable Multi-Agent Reinforcement Learning Framework for Motion Planning
by: Xu, Jianye, et al.
Published: (2024)

Multi-Agent Coordination via Multi-Level Communication
by: Ding, Ziluo, et al.
Published: (2022)

LEED: A Highly Efficient and Scalable LLM-Empowered Expert Demonstrations Framework for Multi-Agent Reinforcement Learning
by: Duan, Tianyang, et al.
Published: (2025)

CAMMARL: Conformal Action Modeling in Multi Agent Reinforcement Learning
by: Gupta, Nikunj, et al.
Published: (2023)

Representation Learning For Efficient Deep Multi-Agent Reinforcement Learning
by: Huh, Dom, et al.
Published: (2024)

Multi-Agent Model-Based Reinforcement Learning with Joint State-Action Learned Embeddings
by: Wang, Zhizun, et al.
Published: (2026)

Multi-Agent Craftax: Benchmarking Open-Ended Multi-Agent Reinforcement Learning at the Hyperscale
by: Omari, Bassel Al, et al.
Published: (2025)

Safe Multi-agent Reinforcement Learning with Natural Language Constraints
by: Wang, Ziyan, et al.
Published: (2024)

Focusing Influence Mechanism for Multi-Agent Reinforcement Learning
by: Park, Yisak, et al.
Published: (2025)

Trajectory-Class-Aware Multi-Agent Reinforcement Learning
by: Na, Hyungho, et al.
Published: (2025)

An Initial Introduction to Cooperative Multi-Agent Reinforcement Learning
by: Amato, Christopher
Published: (2024)

Fully Independent Communication in Multi-Agent Reinforcement Learning
by: Pina, Rafael, et al.
Published: (2024)

Interactive Distillation for Cooperative Multi-Agent Reinforcement Learning
by: Cho, Minwoo, et al.
Published: (2026)

Double Distillation Network for Multi-Agent Reinforcement Learning
by: Zhou, Yang, et al.
Published: (2025)

GAWM: Global-Aware World Model for Multi-Agent Reinforcement Learning
by: Shi, Zifeng, et al.
Published: (2025)

Language Agents with Reinforcement Learning for Strategic Play in the Werewolf Game
by: Xu, Zelai, et al.
Published: (2023)

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

Learning to Coordinate via Quantum Entanglement in Multi-Agent Reinforcement Learning
by: Gardiner, John, et al.
Published: (2026)

Continuous-Time Value Iteration for Multi-Agent Reinforcement Learning
by: Wang, Xuefeng, et al.
Published: (2025)

Events as Triggers for Behavioral Diversity in Multi-Agent Reinforcement Learning
by: Büchi, Hannes, et al.
Published: (2026)

Multi Agent Reinforcement Learning for Sequential Satellite Assignment Problems
by: Holder, Joshua, et al.
Published: (2024)

Stronger-MAS: Multi-Agent Reinforcement Learning for Collaborative LLMs
by: Zhao, Yujie, et al.
Published: (2025)

Hierarchical Lead Critic based Multi-Agent Reinforcement Learning
by: Eckel, David, et al.
Published: (2026)

A Tensor Network Implementation of Multi Agent Reinforcement Learning
by: Howard, Sunny
Published: (2024)

A Survey of Multi-Agent Deep Reinforcement Learning with Communication
by: Zhu, Changxi, et al.
Published: (2022)