:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Yang, Joshua C., Flechtner, Maurice, Dailisan, Damian, Bakker, Michiel A.
Format:	Preprint
Published:	2026
Subjects:	Artificial Intelligence Machine Learning Multiagent Systems
Online Access:	https://arxiv.org/abs/2605.15343
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Mixture-of-Models: Unifying Heterogeneous Agents via N-Way Self-Evaluating Deliberation
by: Pecerskis, Tims, et al.
Published: (2026)

Active Learning for Communication Structure Optimization in LLM-Based Multi-Agent Systems
by: Yang, Huchen, et al.
Published: (2026)

GoAgent: Group-of-Agents Communication Topology Generation for LLM-based Multi-Agent Systems
by: Chen, Hongjiang, et al.
Published: (2026)

LLM-Guided Communication for Cooperative Multi-Agent Reinforcement Learning
by: Bae, Sangjun, et al.
Published: (2026)

Multi-Agent Path Finding via Offline RL and LLM Collaboration
by: Atasever, Merve, et al.
Published: (2025)

MATE: LLM-Powered Multi-Agent Translation Environment for Accessibility Applications
by: Algazinov, Aleksandr, et al.
Published: (2025)

Topological Structure Learning Should Be A Research Priority for LLM-Based Multi-Agent Systems
by: Yang, Jiaxi, et al.
Published: (2025)

Dynamic Sight Range Selection in Multi-Agent Reinforcement Learning
by: Liao, Wei-Chen, et al.
Published: (2025)

OMAC: A Holistic Optimization Framework for LLM-Based Multi-Agent Collaboration
by: Li, Shijun, et al.
Published: (2025)

Dynamic Speculative Agent Planning
by: Guan, Yilin, et al.
Published: (2025)

Talk Structurally, Act Hierarchically: A Collaborative Framework for LLM Multi-Agent Systems
by: Wang, Zhao, et al.
Published: (2025)

Norm-Governed Multi-Agent Decision-Making in Simulator-Coupled Environments:The Reinsurance Constrained Multi-Agent Simulation Process (R-CMASP)
by: Dong, Stella C.
Published: (2025)

Learning Generalizable Skills from Offline Multi-Task Data for Multi-Agent Cooperation
by: Liu, Sicong, et al.
Published: (2025)

DR. WELL: Dynamic Reasoning and Learning with Symbolic World Model for Embodied LLM-Based Multi-Agent Collaboration
by: Nourzad, Narjes, et al.
Published: (2025)

Descent-Guided Policy Gradient for Scalable Cooperative Multi-Agent Learning
by: Yang, Shan, et al.
Published: (2026)

Dynamic Pricing in High-Speed Railways Using Multi-Agent Reinforcement Learning
by: Villarrubia-Martin, Enrique Adrian, et al.
Published: (2025)

EngiAI: A Multi-Agent Framework and Benchmark Suite for LLM-Driven Engineering Design
by: Molinari, Gioele, et al.
Published: (2026)

MedAgentBench: A Realistic Virtual EHR Environment to Benchmark Medical LLM Agents
by: Jiang, Yixing, et al.
Published: (2025)

CleanAgent: Automating Data Standardization with LLM-based Agents
by: Qi, Danrui, et al.
Published: (2024)

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

DynaSwarm: Dynamically Graph Structure Selection for LLM-based Multi-agent System
by: Leong, Hui Yi, et al.
Published: (2025)

Prosociality by Coupling, Not Mere Observation: Homeostatic Sharing in an Inspectable Recurrent Artificial Life Agent
by: Sanyal, Aishik
Published: (2026)

LERO: LLM-driven Evolutionary framework with Hybrid Rewards and Enhanced Observation for Multi-Agent Reinforcement Learning
by: Wei, Yuan, et al.
Published: (2025)

Collaborative Memory: Multi-User Memory Sharing in LLM Agents with Dynamic Access Control
by: Rezazadeh, Alireza, et al.
Published: (2025)

Agent-Oriented Planning in Multi-Agent Systems
by: Li, Ao, et al.
Published: (2024)

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

SAMVAD: A Multi-Agent System for Simulating Judicial Deliberation Dynamics in India
by: Devadiga, Prathamesh, et al.
Published: (2025)

The Yokai Learning Environment: Tracking Beliefs Over Space and Time
by: Ruhdorfer, Constantin, et al.
Published: (2025)

KernelSkill: A Multi-Agent Framework for GPU Kernel Optimization
by: Sun, Qitong, et al.
Published: (2026)

AutoSurrogate: An LLM-Driven Multi-Agent Framework for Autonomous Construction of Deep Learning Surrogate Models in Subsurface Flow
by: Liu, Jiale, et al.
Published: (2026)

MasHost Builds It All: Autonomous Multi-Agent System Directed by Reinforcement Learning
by: Yang, Kuo, et al.
Published: (2025)

Multi-Agent Decision Transformers for Dynamic Dispatching in Material Handling Systems Leveraging Enterprise Big Data
by: Lee, Xian Yeow, et al.
Published: (2024)

Heterogeneous Information-Bottleneck Coordination Graphs for Multi-Agent Reinforcement Learning
by: Duan, Wei, et al.
Published: (2026)

Verifiability-First Agents: Provable Observability and Lightweight Audit Agents for Controlling Autonomous LLM Systems
by: Gupta, Abhivansh
Published: (2025)

Multi-Agent Reinforcement Learning Meets Leaf Sequencing in Radiotherapy
by: Gao, Riqiang, et al.
Published: (2024)

Frontier Coding Agents Can Now Implement an AlphaZero Self-Play Machine Learning Pipeline For Connect Four That Performs Comparably to an External Solver
by: Sherwood, Joshua, et al.
Published: (2026)

Distributed Deep Reinforcement Learning: A Survey and A Multi-Player Multi-Agent Learning Toolbox
by: Yin, Qiyue, et al.
Published: (2022)

Goal-Oriented Multi-Agent Reinforcement Learning for Decentralized Agent Teams
by: Du, Hung, et al.
Published: (2025)

PTDE: Personalized Training with Distilled Execution for Multi-Agent Reinforcement Learning
by: Chen, Yiqun, et al.
Published: (2022)

Context Learning for Multi-Agent Discussion
by: Hua, Xingyuan, et al.
Published: (2026)