Imagen de Portada

ReCollab: Retrieval-Augmented LLMs for Cooperative Ad-hoc Teammate Modeling

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Wallace, Conor, Siddique, Umer, Cao, Yongcan
Formato:	Preprint
Publicado:	2025
Materias:	Multiagent Systems Artificial Intelligence Machine Learning
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

TransAM: Transformer-Based Agent Modeling for Multi-Agent Systems via Local Trajectory Encoding
por: Wallace, Conor, et al.
Publicado: (2025)

Adaptive Event-Triggered Policy Gradient for Multi-Agent Reinforcement Learning
por: Siddique, Umer, et al.
Publicado: (2025)

From Explainability to Interpretability: Interpretable Policies in Reinforcement Learning Via Model Explanation
por: Li, Peilang, et al.
Publicado: (2025)

Speculative Ad-hoc Querying
por: Li, Haoyu, et al.
Publicado: (2025)

Adaptive Event-triggered Reinforcement Learning Control for Complex Nonlinear Systems
por: Siddique, Umer, et al.
Publicado: (2024)

CooperBench: Why Coding Agents Cannot be Your Teammates Yet
por: Khatua, Arpandeep, et al.
Publicado: (2026)

Unsupervised Partner Design Enables Robust Ad-hoc Teamwork
por: Ruhdorfer, Constantin, et al.
Publicado: (2025)

ProAgent: Building Proactive Cooperative Agents with Large Language Models
por: Zhang, Ceyao, et al.
Publicado: (2023)

Quantum Frog: Emergent Cooperation and Difficulty Scaling in a Quantized-Time Cooperative Game
por: Mankarious, Saad
Publicado: (2026)

Enhancing Cooperative Multi-Agent Reinforcement Learning with State Modelling and Adversarial Exploration
por: Kontogiannis, Andreas, et al.
Publicado: (2025)

Coordination Failure in Cooperative Offline MARL
por: Tilbury, Callum Rhys, et al.
Publicado: (2024)

Cooperative Bayesian Optimization for Imperfect Agents
por: Khoshvishkaie, Ali, et al.
Publicado: (2024)

RecBayes: Recurrent Bayesian Ad Hoc Teamwork in Large Partially Observable Domains
por: Ribeiro, João G., et al.
Publicado: (2025)

CORD: Generalizable Cooperation via Role Diversity
por: Matsuyama, Kanefumi, et al.
Publicado: (2025)

Learning to Cooperate with Humans using Generative Agents
por: Liang, Yancheng, et al.
Publicado: (2024)

When Is Diversity Rewarded in Cooperative Multi-Agent Learning?
por: Amir, Michael, et al.
Publicado: (2025)

COSAC: Counterfactual Credit Assignment in Sequential Cooperative Teams
por: Deshmukh, Shripad, et al.
Publicado: (2026)

Hierarchical Reinforcement Learning for Optimal Agent Grouping in Cooperative Systems
por: Hu, Liyuan
Publicado: (2025)

The Composite Task Challenge for Cooperative Multi-Agent Reinforcement Learning
por: Li, Yurui, et al.
Publicado: (2025)

From Grunts to Lexicons: Emergent Language from Cooperative Foraging
por: Piriyajitakonkij, Maytus, et al.
Publicado: (2025)

Coordination Matters: Evaluation of Cooperative Multi-Agent Reinforcement Learning
por: Cardei, Maria Ana, et al.
Publicado: (2026)

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

Towards Global Optimality in Cooperative MARL with the Transformation And Distillation Framework
por: Ye, Jianing, et al.
Publicado: (2022)

POGEMA: A Benchmark Platform for Cooperative Multi-Agent Pathfinding
por: Skrynnik, Alexey, et al.
Publicado: (2024)

Empirical Study on Robustness and Resilience in Cooperative Multi-Agent Reinforcement Learning
por: Li, Simin, et al.
Publicado: (2025)

Centralized Permutation Equivariant Policy for Cooperative Multi-Agent Reinforcement Learning
por: Xu, Zhuofan, et al.
Publicado: (2025)

Cross-environment Cooperation Enables Zero-shot Multi-agent Coordination
por: Jha, Kunal, et al.
Publicado: (2025)

Anomaly Detection in Cooperative Vehicle Perception Systems under Imperfect Communication
por: Bastola, Ashish, et al.
Publicado: (2025)

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

Fully Decentralized Cooperative Multi-Agent Reinforcement Learning: A Survey
por: Jiang, Jiechuan, et al.
Publicado: (2024)

PIANIST: Learning Partially Observable World Models with LLMs for Multi-Agent Decision Making
por: Light, Jonathan, et al.
Publicado: (2024)

Tacit Learning with Adaptive Information Selection for Cooperative Multi-Agent Reinforcement Learning
por: Liu, Lunjun, et al.
Publicado: (2024)

AIR: Unifying Individual and Collective Exploration in Cooperative Multi-Agent Reinforcement Learning
por: Zhou, Guangchong, et al.
Publicado: (2024)

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

ToMCAT: Theory-of-Mind for Cooperative Agents in Teams via Multiagent Diffusion Policies
por: Sequeira, Pedro, et al.
Publicado: (2025)

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

Investigating the Impact of Direct Punishment on the Emergence of Cooperation in Multi-Agent Reinforcement Learning Systems
por: Dasgupta, Nayana, et al.
Publicado: (2023)

ReMA: Learning to Meta-think for LLMs with Multi-Agent Reinforcement Learning
por: Wan, Ziyu, et al.
Publicado: (2025)

A Survey of Multi Agent Reinforcement Learning: Federated Learning and Cooperative and Noncooperative Decentralized Regimes
por: Cheruiyot, Kemboi, et al.
Publicado: (2025)

${\rm E}(3)$-Equivariant Actor-Critic Methods for Cooperative Multi-Agent Reinforcement Learning
por: Chen, Dingyang, et al.
Publicado: (2023)