Aprendizaje en sistemas multi-agentes para resolver problemas de scheduling: una revisión sistemática de la literatura

G Icarte-Ahumada, J Montoya, Z He - Ingeniare. Revista chilena de …, 2024 - SciELO Chile
Los problemas de scheduling están presentes en varios dominios y requieren una
asignación eficiente de recursos y coordinación de tareas para optimizar el rendimiento y …

Advancing RAN slicing with offline reinforcement learning

K Yang, SP Yeh, M Zhang, J Sydir… - … on Dynamic Spectrum …, 2024 - ieeexplore.ieee.org
Dynamic radio resource management (RRM) in wireless networks presents significant
challenges, particularly in the context of Radio Access Network (RAN) slicing. This …

Learning in multi-agent systems to solve scheduling problems: a systematic literature review

G Icarte-Ahumada, J Montoya… - Ingeniare: Revista Chilena …, 2024 - search.proquest.com
Scheduling problems are ubiquitous in various domains, requiring efficient allocation of
resources and coordination of tasks to optimize performance and meet desired objectives …

Distributed MARL for Scheduling in Conflict Graphs

Y Zhang, D Guo - 2023 59th Annual Allerton Conference on …, 2023 - ieeexplore.ieee.org
This paper addresses a link scheduling problem in networks represented by conflict graphs
using a distributed learning approach. Each agent in a network controls a single link and …

A Scalable MARL Solution for Scheduling in Conflict Graphs

Y Zhang, D Guo - arXiv preprint arXiv:2312.05746, 2023 - arxiv.org
This paper proposes a fully scalable multi-agent reinforcement learning (MARL) approach
for packet scheduling in conflict graphs, aiming to minimizing average packet delays. Each …

Time-Critical Decisions With Real-Time Information Extraction

X Chen - 2023 - search.proquest.com
Abstract The Internet of Things and the next-generation networks have led to the generation,
dissemination, and transformation of a huge amount of real-time information. The …