Cover Image

High-order Interactions Modeling for Interpretable Multi-Agent Q-Learning

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Xu, Qinyu, Zhu, Yuanyang, Wu, Xuefei, Chen, Chunlin
Format:	Preprint
Published:	2025
Subjects:	Multiagent Systems Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Learning Individual Intrinsic Reward in Multi-Agent Reinforcement Learning via Incorporating Generalized Human Expertise
by: Wu, Xuefei, et al.
Published: (2025)

N$\text{A}^\text{2}$Q: Neural Attention Additive Model for Interpretable Multi-Agent Q-Learning
by: Liu, Zichuan, et al.
Published: (2023)

MIXRTs: Toward Interpretable Multi-Agent Reinforcement Learning via Mixing Recurrent Soft Decision Trees
by: Liu, Zichuan, et al.
Published: (2022)

Interpreting Emergent Extreme Events in Multi-Agent Systems
by: Tang, Ling, et al.
Published: (2026)

Heterogeneous Interaction Modeling With Reduced Accumulated Error for Multi-Agent Trajectory Prediction
by: Chen, Siyuan, et al.
Published: (2024)

CityGPT: Towards Urban IoT Learning, Analysis and Interaction with Multi-Agent System
by: Guan, Qinghua, et al.
Published: (2024)

XAgents: A Framework for Interpretable Rule-Based Multi-Agents Cooperation
by: Yang, Hailong, et al.
Published: (2024)

SocialGFs: Learning Social Gradient Fields for Multi-Agent Reinforcement Learning
by: Long, Qian, et al.
Published: (2024)

Multi-agent Reinforcement Learning with Deep Networks for Diverse Q-Vectors
by: Luo, Zhenglong, et al.
Published: (2024)

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

IFPV: An Integrated Multi-Agent Framework for Generative Operational Planning and High-Fidelity Plan Verification
by: Huang, Zhigao, et al.
Published: (2026)

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

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 Training for Pommerman: Curriculum Learning and Population-based Self-Play Approach
by: Huynh, Nhat-Minh, et al.
Published: (2024)

OPTAGENT: Optimizing Multi-Agent LLM Interactions Through Verbal Reinforcement Learning for Enhanced Reasoning
by: Bi, Zhenyu, et al.
Published: (2025)

Who's the Mole? Modeling and Detecting Intention-Hiding Malicious Agents in LLM-Based Multi-Agent Systems
by: Xie, Yizhe, et al.
Published: (2025)

Single-Agent Scaling Fails Multi-Agent Intelligence: Towards Foundation Models with Native Multi-Agent Intelligence
by: Hu, Shuyue, et al.
Published: (2025)

Interaction Pattern Disentangling for Multi-Agent Reinforcement Learning
by: Liu, Shunyu, et al.
Published: (2022)

From Spark to Fire: Modeling and Mitigating Error Cascades in LLM-Based Multi-Agent Collaboration
by: Xie, Yizhe, et al.
Published: (2026)

Towards Scientific Intelligence: A Survey of LLM-based Scientific Agents
by: Ren, Shuo, et al.
Published: (2025)

Beyond Local Views: Global State Inference with Diffusion Models for Cooperative Multi-Agent Reinforcement Learning
by: Xu, Zhiwei, et al.
Published: (2024)

Interactional Fairness in LLM Multi-Agent Systems: An Evaluation Framework
by: Binkyte, Ruta
Published: (2025)

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

Embodiment-Induced Coordination Regimes in Tabular Multi-Agent Q-Learning
by: Atif, Muhammad Ahmed, et al.
Published: (2026)

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

Interpretable Failure Analysis in Multi-Agent Reinforcement Learning Systems
by: Shefin, Risal Shahriar, et al.
Published: (2026)

Detecting Multi-Agent Collusion Through Multi-Agent Interpretability
by: Rose, Aaron, et al.
Published: (2026)

Multi-Agent Inverse Q-Learning from Demonstrations
by: Haynam, Nathaniel, et al.
Published: (2025)

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

AgentArk: Distilling Multi-Agent Intelligence into a Single LLM Agent
by: Luo, Yinyi, et al.
Published: (2026)

Multi-Agent Continuous Control with Generative Flow Networks
by: Luo, Shuang, et al.
Published: (2024)

MedCollab: IBIS-Guided Multi-Agent Collaboration with Hierarchical Disease Relation Chains for Clinical Diagnosis
by: Zhan, Yuqi, et al.
Published: (2026)

Interacting Large Language Model Agents. Interpretable Models and Social Learning
by: Jain, Adit, et al.
Published: (2024)

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

AgentMixer: Multi-Agent Correlated Policy Factorization
by: Li, Zhiyuan, et al.
Published: (2024)

Understanding Individual Agent Importance in Multi-Agent System via Counterfactual Reasoning
by: Chen, Jianming, et al.
Published: (2024)

From Single to Societal: Analyzing Persona-Induced Bias in Multi-Agent Interactions
by: Li, Jiayi, et al.
Published: (2025)

The Bystander Effect in Multi-Agent Reasoning: Quantifying Cognitive Loafing in Collaborative Interactions
by: Shehata, Dahlia, et al.
Published: (2026)

Enhancing LLM Problem Solving via Tutor-Student Multi-Agent Interaction
by: Özdemir, Nurullah Eymen, et al.
Published: (2026)