:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Adhikari, Noah, Gu, Allen
Format:	Preprint
Published:	2024
Subjects:	Artificial Intelligence
Online Access:	https://arxiv.org/abs/2405.18733
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Prism: Spectral Parameter Sharing for Multi-Agent Reinforcement Learning
by: Kim, Kyungbeom, et al.
Published: (2026)

PPS-QMIX: Periodically Parameter Sharing for Accelerating Convergence of Multi-Agent Reinforcement Learning
by: Zhang, Ke, et al.
Published: (2024)

Robust and Efficient Communication in Multi-Agent Reinforcement Learning
by: Liu, Zejiao, et al.
Published: (2025)

Selectively Sharing Experiences Improves Multi-Agent Reinforcement Learning
by: Gerstgrasser, Matthias, et al.
Published: (2023)

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

Contextual Knowledge Sharing in Multi-Agent Reinforcement Learning with Decentralized Communication and Coordination
by: Du, Hung, et al.
Published: (2025)

Linear Bellman Completeness Suffices for Efficient Online Reinforcement Learning with Few Actions
by: Golowich, Noah, et al.
Published: (2024)

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

Achieving Collective Welfare in Multi-Agent Reinforcement Learning via Suggestion Sharing
by: Jin, Yue, et al.
Published: (2024)

Concept Learning for Cooperative Multi-Agent Reinforcement Learning
by: Ge, Zhonghan, et al.
Published: (2025)

MoSLD: An Extremely Parameter-Efficient Mixture-of-Shared LoRAs for Multi-Task Learning
by: Zhao, Lulu, et al.
Published: (2024)

On Centralized Critics in Multi-Agent Reinforcement Learning
by: Lyu, Xueguang, et al.
Published: (2024)

Reinforcement Learning with Foundation Priors: Let the Embodied Agent Efficiently Learn on Its Own
by: Ye, Weirui, et al.
Published: (2023)

Multi-Task Reinforcement Learning Enables Parameter Scaling
by: McLean, Reginald, et al.
Published: (2025)

A Robust and Efficient Multi-Agent Reinforcement Learning Framework for Traffic Signal Control
by: Huang, Sheng-You, et al.
Published: (2026)

Heterogeneity in Multi-Agent Reinforcement Learning
by: Hu, Tianyi, et al.
Published: (2025)

Multi-Agent Reinforcement Learning for Autonomous Driving: A Survey
by: Zhang, Ruiqi, et al.
Published: (2024)

Parameter Efficient Reinforcement Learning from Human Feedback
by: Sidahmed, Hakim, et al.
Published: (2024)

On Stateful Value Factorization in Multi-Agent Reinforcement Learning
by: Marchesini, Enrico, et al.
Published: (2024)

Adaptive Robust Estimator for Multi-Agent Reinforcement Learning
by: Li, Zhongyi, et al.
Published: (2026)

Explaining Decentralized Multi-Agent Reinforcement Learning Policies
by: Boggess, Kayla, et al.
Published: (2025)

Coordination Graphs for Constrained Multi-Agent Reinforcement Learning
by: Amaya-Corredor, Santiago, et al.
Published: (2026)

Toward Dependency Dynamics in Multi-Agent Reinforcement Learning for Traffic Signal Control
by: Zhang, Yuli, et al.
Published: (2025)

Scalable Safe Multi-Agent Reinforcement Learning for Multi-Agent System
by: Du, Haikuo, et al.
Published: (2025)

Comparative Analysis of Multi-Agent Reinforcement Learning Policies for Crop Planning Decision Support
by: Mahajan, Anubha, et al.
Published: (2024)

Pretraining a Shared Q-Network for Data-Efficient Offline Reinforcement Learning
by: Park, Jongchan, et al.
Published: (2025)

LLM Collaboration With Multi-Agent Reinforcement Learning
by: Liu, Shuo, et al.
Published: (2025)

CP-SynC: Multi-Agent Zero-Shot Constraint Modeling in MiniZinc with Synthesized Checkers
by: Song, Yuliang, et al.
Published: (2026)

MA4DIV: Multi-Agent Reinforcement Learning for Search Result Diversification
by: Chen, Yiqun, et al.
Published: (2024)

LEMON: Learning Executable Multi-Agent Orchestration via Counterfactual Reinforcement Learning
by: Chen, Xudong, et al.
Published: (2026)

Efficient On-Policy Reinforcement Learning via Exploration of Sparse Parameter Space
by: Zhang, Xinyu, et al.
Published: (2025)

Symmetry-Guided Multi-Agent Inverse Reinforcement Learning
by: Tian, Yongkai, et al.
Published: (2025)

Efficient Training in Multi-Agent Reinforcement Learning: A Communication-Free Framework for the Box-Pushing Problem
by: Ge, David, et al.
Published: (2024)

PyTAG: Tabletop Games for Multi-Agent Reinforcement Learning
by: Balla, Martin, et al.
Published: (2024)

Perspectives for Direct Interpretability in Multi-Agent Deep Reinforcement Learning
by: Poupart, Yoann, et al.
Published: (2025)

MARL-GPT: Foundation Model for Multi-Agent Reinforcement Learning
by: Nesterova, Maria, et al.
Published: (2026)

The Multi-Agent Reinforcement Learning in MalmÖ (MARLÖ) Competition
by: Perez-Liebana, Diego, et al.
Published: (2019)

MEAL: A Benchmark for Continual Multi-Agent Reinforcement Learning
by: Tomilin, Tristan, et al.
Published: (2025)

Pessimistic Value Iteration for Multi-Task Data Sharing in Offline Reinforcement Learning
by: Bai, Chenjia, et al.
Published: (2024)

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