Cover Image

Multi-agent Reinforcement Learning with Deep Networks for Diverse Q-Vectors

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Luo, Zhenglong, Chen, Zhiyong, Welsh, James
Format:	Preprint
Published:	2024
Subjects:	Artificial Intelligence Multiagent Systems
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Graph Neural Networks with Model-based Reinforcement Learning for Multi-agent Systems
by: Chen, Hanxiao
Published: (2024)

GHQ: Grouped Hybrid Q Learning for Heterogeneous Cooperative Multi-agent Reinforcement Learning
by: Yu, Xiaoyang, et al.
Published: (2023)

Verco: Learning Coordinated Verbal Communication for Multi-agent Reinforcement Learning
by: Li, Dapeng, et al.
Published: (2024)

Scalable Multi-agent Reinforcement Learning for Factory-wide Dynamic Scheduling
by: Jang, Jaeyeon, et al.
Published: (2024)

Nucleolus Credit Assignment for Effective Coalitions in Multi-agent Reinforcement Learning
by: Li, Yugu, et al.
Published: (2025)

Learning to Deliberate: Meta-policy Collaboration for Agentic LLMs with Multi-agent Reinforcement Learning
by: Yang, Wei, et al.
Published: (2025)

Constructive Conflict-Driven Multi-Agent Reinforcement Learning for Strategic Diversity
by: Mai, Yuxiang, et al.
Published: (2025)

Efficient Multi-agent Reinforcement Learning by Planning
by: Liu, Qihan, et al.
Published: (2024)

Towards Multi-agent Reinforcement Learning based Traffic Signal Control through Spatio-temporal Hypergraphs
by: Wang, Kang, et al.
Published: (2024)

Improving Global Parameter-sharing in Physically Heterogeneous Multi-agent Reinforcement Learning with Unified Action Space
by: Yu, Xiaoyang, et al.
Published: (2024)

High-order Interactions Modeling for Interpretable Multi-Agent Q-Learning
by: Xu, Qinyu, et al.
Published: (2025)

Joint Intrinsic Motivation for Coordinated Exploration in Multi-Agent Deep Reinforcement Learning
by: Toquebiau, Maxime, et al.
Published: (2024)

Graph Based Deep Reinforcement Learning Aided by Transformers for Multi-Agent Cooperation
by: Elrod, Michael, et al.
Published: (2025)

Multi-agent Reinforcement Learning: A Comprehensive Survey
by: Huh, Dom, et al.
Published: (2023)

Multi-Agent Target Assignment and Path Finding for Intelligent Warehouse: A Cooperative Multi-Agent Deep Reinforcement Learning Perspective
by: Liu, Qi, et al.
Published: (2024)

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

Multi-Agent Reinforcement Learning Simulation for Environmental Policy Synthesis
by: Rudd-Jones, James, et al.
Published: (2025)

Fair Compromises in Participatory Budgeting: a Multi-Agent Deep Reinforcement Learning Approach
by: Adams, Hugh, et al.
Published: (2025)

MO-MIX: Multi-Objective Multi-Agent Cooperative Decision-Making With Deep Reinforcement Learning
by: Hu, Tianmeng, et al.
Published: (2026)

NetSafe: Exploring the Topological Safety of Multi-agent Networks
by: Yu, Miao, et al.
Published: (2024)

Kaleidoscope: Learnable Masks for Heterogeneous Multi-agent Reinforcement Learning
by: Li, Xinran, et al.
Published: (2024)

Episodic Future Thinking Mechanism for Multi-agent Reinforcement Learning
by: Lee, Dongsu, et al.
Published: (2024)

Achieving Equilibrium under Utility Heterogeneity: An Agent-Attention Framework for Multi-Agent Multi-Objective Reinforcement Learning
by: Li, Zhuhui, et al.
Published: (2025)

QSIM: Mitigating Overestimation in Multi-Agent Reinforcement Learning via Action Similarity Weighted Q-Learning
by: Li, Yuanjun, et al.
Published: (2026)

Multi-Agent Reinforcement Learning with Communication-Constrained Priors
by: Yang, Guang, et al.
Published: (2025)

Multi-agent Reinforcement Learning for Dynamic Dispatching in Material Handling Systems
by: Lee, Xian Yeow, et al.
Published: (2024)

Exponential Topology-enabled Scalable Communication in Multi-agent Reinforcement Learning
by: Li, Xinran, et al.
Published: (2025)

Model-based Multi-agent Reinforcement Learning: Recent Progress and Prospects
by: Wang, Xihuai, et al.
Published: (2022)

RiskQ: Risk-sensitive Multi-Agent Reinforcement Learning Value Factorization
by: Shen, Siqi, et al.
Published: (2023)

Vulnerable Agent Identification in Large-Scale Multi-Agent Reinforcement Learning
by: Li, Simin, et al.
Published: (2025)

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

A Survey of Multi-Agent Deep Reinforcement Learning with Graph Neural Network-Based Communication
by: Cuzin-Rambaud, Valentin, et al.
Published: (2026)

Multi-source Plume Tracing via Multi-Agent Reinforcement Learning
by: Granadeno, Pedro Antonio Alarcon, et al.
Published: (2025)

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

PeroMAS: A Multi-agent System of Perovskite Material Discovery
by: Wang, Yishu, et al.
Published: (2026)

Controlling Behavioral Diversity in Multi-Agent Reinforcement Learning
by: Bettini, Matteo, et al.
Published: (2024)

NaviGNN: Multi-Agent Reinforcement Learning and Graph Neural Network for Sustainable Mobility in Futuristic Smart Cities
by: Bahi, Abderaouf, et al.
Published: (2025)

QLLM: Do We Really Need a Mixing Network for Credit Assignment in Multi-Agent Reinforcement Learning?
by: Li, Yuanjun, et al.
Published: (2025)

Measuring Policy Distance for Multi-Agent Reinforcement Learning
by: Hu, Tianyi, et al.
Published: (2024)

Causal Mean Field Multi-Agent Reinforcement Learning
by: Ma, Hao, et al.
Published: (2025)