Copertina

Maestro: Learning to Collaborate via Conditional Listwise Policy Optimization for Multi-Agent LLMs

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Yang, Wei, Pang, Jiacheng, Li, Shixuan, Bogdan, Paul, Tu, Stephen, Thomason, Jesse
Natura:	Preprint
Pubblicazione:	2025
Soggetti:	Artificial Intelligence Multiagent Systems
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

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

Evaluating Creativity and Deception in Large Language Models: A Simulation Framework for Multi-Agent Balderdash
di: Hejabi, Parsa, et al.
Pubblicazione: (2024)

Collaborative Belief Reasoning with LLMs for Efficient Multi-Agent Collaboration
di: Wang, Zhimin, et al.
Pubblicazione: (2025)

Agent-GSPO: Communication-Efficient Multi-Agent Systems via Group Sequence Policy Optimization
di: Fan, Yijia, et al.
Pubblicazione: (2025)

Multi-Agent Guided Policy Optimization
di: Li, Yueheng, et al.
Pubblicazione: (2025)

RobotFleet: An Open-Source Framework for Centralized Multi-Robot Task Planning
di: Gupta, Rohan, et al.
Pubblicazione: (2025)

Optimizing Agent Collaboration through Heuristic Multi-Agent Planning
di: Soffair, Nitsan
Pubblicazione: (2023)

Weak-Link Optimization for Multi-Agent Reasoning and Collaboration
di: Bian, Haoyu, et al.
Pubblicazione: (2026)

GRASP: Gradient Realignment via Active Shared Perception for Multi-Agent Collaborative Optimization
di: Zhou, Sihan, et al.
Pubblicazione: (2026)

TwoStep: Multi-agent Task Planning using Classical Planners and Large Language Models
di: Bai, David, et al.
Pubblicazione: (2024)

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

An Empirical Study of Multi-Agent Collaboration for Automated Research
di: Shen, Yang, et al.
Pubblicazione: (2026)

Safe Equilibrium Policy Optimization for Strategic Agent Policies
di: Arumugam, Karthika, et al.
Pubblicazione: (2026)

CCL: Collaborative Curriculum Learning for Sparse-Reward Multi-Agent Reinforcement Learning via Co-evolutionary Task Evolution
di: Lin, Yufei, et al.
Pubblicazione: (2025)

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

Multi-Agent Collaboration via Evolving Orchestration
di: Dang, Yufan, et al.
Pubblicazione: (2025)

AgentCDM: Enhancing Multi-Agent Collaborative Decision-Making via ACH-Inspired Structured Reasoning
di: Zhao, Xuyang, et al.
Pubblicazione: (2025)

Influencing LLM Multi-Agent Dialogue via Policy-Parameterized Prompts
di: Bo, Hongbo, et al.
Pubblicazione: (2026)

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

MPAC: A Multi-Principal Agent Coordination Protocol for Interoperable Multi-Agent Collaboration
di: Qian, Kaiyang, et al.
Pubblicazione: (2026)

Counterfactual Multi-Agent Policy Gradients
di: Foerster, Jakob, et al.
Pubblicazione: (2017)

MALBO: Optimizing LLM-Based Multi-Agent Teams via Multi-Objective Bayesian Optimization
di: Sabbatella, Antonio
Pubblicazione: (2025)

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

The Consensus Trap: Rescuing Multi-Agent LLMs from Adversarial Majorities via Token-Level Collaboration
di: Liu, Jiayuan, et al.
Pubblicazione: (2026)

Multi-Agent Security Tax: Trading Off Security and Collaboration Capabilities in Multi-Agent Systems
di: Peigne-Lefebvre, Pierre, et al.
Pubblicazione: (2025)

MACC: Multi-Agent Collaborative Competition for Scientific Exploration
di: Oyama, Satoshi, et al.
Pubblicazione: (2026)

BMW Agents -- A Framework For Task Automation Through Multi-Agent Collaboration
di: Crawford, Noel, et al.
Pubblicazione: (2024)

DDO: Dual-Decision Optimization for LLM-Based Medical Consultation via Multi-Agent Collaboration
di: Jia, Zhihao, et al.
Pubblicazione: (2025)

TAPE: Leveraging Agent Topology for Cooperative Multi-Agent Policy Gradient
di: Lou, Xingzhou, et al.
Pubblicazione: (2023)

CREW-WILDFIRE: Benchmarking Agentic Multi-Agent Collaborations at Scale
di: Hyun, Jonathan, et al.
Pubblicazione: (2025)

HAWK: A Hierarchical Workflow Framework for Multi-Agent Collaboration
di: Cheng, Yuyang, et al.
Pubblicazione: (2025)

Beyond Frameworks: Unpacking Collaboration Strategies in Multi-Agent Systems
di: Wang, Haochun, et al.
Pubblicazione: (2025)

MultiAgent Collaboration Attack: Investigating Adversarial Attacks in Large Language Model Collaborations via Debate
di: Amayuelas, Alfonso, et al.
Pubblicazione: (2024)

Generalizable Agent Modeling for Agent Collaboration-Competition Adaptation with Multi-Retrieval and Dynamic Generation
di: Wang, Chenxu, et al.
Pubblicazione: (2025)

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

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

Decentralized and Lifelong-Adaptive Multi-Agent Collaborative Learning
di: Tang, Shuo, et al.
Pubblicazione: (2024)

Data-Efficient Multi-Agent Spatial Planning with LLMs
di: Su, Huangyuan, et al.
Pubblicazione: (2025)

Towards CausalGPT: A Multi-Agent Approach for Faithful Knowledge Reasoning via Promoting Causal Consistency in LLMs
di: Tang, Ziyi, et al.
Pubblicazione: (2023)

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