Imagen de Portada

SPECTra: Scalable Multi-Agent Reinforcement Learning with Permutation-Free Networks

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Park, Hyunwoo, Seong, Baekryun, Ko, Sang-Ki
Formato:	Preprint
Publicado:	2025
Materias:	Machine Learning Artificial Intelligence I.2.11
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

Communication Methods in Multi-Agent Reinforcement Learning
por: Wittner, Christoph
Publicado: (2026)

Risk-Sensitive Multi-Agent Reinforcement Learning in Network Aggregative Markov Games
por: Ghaemi, Hafez, et al.
Publicado: (2024)

Multi-Agent Reinforcement Learning with Selective State-Space Models
por: Daniel, Jemma, et al.
Publicado: (2024)

TwinLoop: Simulation-in-the-Loop Digital Twins for Online Multi-Agent Reinforcement Learning
por: Zhang, Nan, et al.
Publicado: (2026)

Tazza: Shuffling Neural Network Parameters for Secure and Private Federated Learning
por: Lee, Kichang, et al.
Publicado: (2024)

Generative Evolutionary Meta-Solver (GEMS): Scalable Surrogate-Free Multi-Agent Reinforcement Learning
por: Sharma, Alakh, et al.
Publicado: (2025)

A Scalable Communication Protocol for Networks of Large Language Models
por: Marro, Samuele, et al.
Publicado: (2024)

A Principle of Targeted Intervention for Multi-Agent Reinforcement Learning
por: Liu, Anjie, et al.
Publicado: (2025)

MACS: Multi-Agent Reinforcement Learning for Optimization of Crystal Structures
por: Zamaraeva, Elena, et al.
Publicado: (2025)

Improving Local Training in Federated Learning via Temperature Scaling
por: Lee, Kichang, et al.
Publicado: (2024)

FlowSteer: Towards Agents Designing Agentic Workflows via Reinforced Progressive Canvas Editing
por: Zhang, Mingda, et al.
Publicado: (2026)

Extending NGU to Multi-Agent RL: A Preliminary Study
por: Hernandez, Juan, et al.
Publicado: (2025)

Exploring Robust Multi-Agent Workflows for Environmental Data Management
por: Guan, Boyuan, et al.
Publicado: (2026)

MOSS: Self-Evolution through Source-Level Rewriting in Autonomous Agent Systems
por: Cai, Qianshu, et al.
Publicado: (2026)

When Actions Disappear: Adversarial Action Removal in Self-Play Reinforcement Learning
por: Kujur, Arahan
Publicado: (2026)

Reinforcement Learning for Scalable and Trustworthy Intelligent Systems
por: Lan, Guangchen
Publicado: (2026)

FedNoisy: Federated Noisy Label Learning Benchmark
por: Liang, Siqi, et al.
Publicado: (2023)

Individual Contributions as Intrinsic Exploration Scaffolds for Multi-agent Reinforcement Learning
por: Li, Xinran, et al.
Publicado: (2024)

Networked Agents in the Dark: Team Value Learning under Partial Observability
por: Varela, Guilherme S., et al.
Publicado: (2025)

Distributed Value Decomposition Networks with Networked Agents
por: Varela, Guilherme S., et al.
Publicado: (2025)

Graphon Mean-Field Subsampling for Cooperative Heterogeneous Multi-Agent Reinforcement Learning
por: Anand, Emile, et al.
Publicado: (2026)

FedHPD: Heterogeneous Federated Reinforcement Learning via Policy Distillation
por: Jiang, Wenzheng, et al.
Publicado: (2025)

Agent Capsules: Quality-Gated Granularity Control for Multi-Agent LLM Pipelines
por: Ray, Aninda
Publicado: (2026)

ME-IGM: Individual-Global-Max in Maximum Entropy Multi-Agent Reinforcement Learning
por: Chen, Wen-Tse, et al.
Publicado: (2024)

Dynamic Attentional Context Scoping: Agent-Triggered Focus Sessions for Isolated Per-Agent Steering in Multi-Agent LLM Orchestration
por: Patel, Nickson
Publicado: (2026)

Collaboration Promotes Group Resilience in Multi-Agent RL
por: Shraga, Ilai, et al.
Publicado: (2021)

MMiC: Mitigating Modality Incompleteness in Clustered Federated Learning
por: Yang, Lishan, et al.
Publicado: (2025)

Dynamical Priors as a Training Objective in Reinforcement Learning
por: Subaharan, Sukesh
Publicado: (2026)

Which LLM Multi-Agent Protocol to Choose?
por: Du, Hongyi, et al.
Publicado: (2025)

AgensFlow: A Coordination-Policy Substrate for Multi-Agent Systems
por: Koenigstein, Nicole
Publicado: (2026)

Improving Generalization in Heterogeneous Federated Continual Learning via Spatio-Temporal Gradient Matching with Prototypical Coreset
por: Nguyen, Minh-Duong, et al.
Publicado: (2025)

Temperature Scaling Attack Disrupting Model Confidence in Federated Learning
por: Lee, Kichang, et al.
Publicado: (2026)

Representational Collapse in Multi-Agent LLM Committees: Measurement and Diversity-Aware Consensus
por: Patel, Dipkumar
Publicado: (2026)

PRIMA: Operational Patterns for Resilient Multi-Agent Research with Verifiable Identity and Convergent Feedback
por: Annapureddy, Sasank
Publicado: (2026)

Centrally Coordinated Multi-Agent Reinforcement Learning for Power Grid Topology Control
por: de Mol, Barbera, et al.
Publicado: (2025)

Knowledge Transfer in Model-Based Reinforcement Learning Agents for Efficient Multi-Task Learning
por: Kuzmenko, Dmytro, et al.
Publicado: (2025)

Decentralized Multi-Agent Active Search and Tracking when Targets Outnumber Agents
por: Banerjee, Arundhati, et al.
Publicado: (2024)

Robust and Diverse Multi-Agent Learning via Rational Policy Gradient
por: Lauffer, Niklas, et al.
Publicado: (2025)

EvoMAS: Evolutionary Generation of Multi-Agent Systems
por: Hu, Yuntong, et al.
Publicado: (2026)

FediLoRA: Practical Federated Fine-Tuning of Foundation Models Under Missing-Modality Constraints
por: Yang, Lishan, et al.
Publicado: (2025)