GCEN: Multi-agent deep reinforcement learning with grouped cognitive feature representation

H Gao, X Xu, C Yan, Y Lan… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
In recent years, cooperative multiagent deep reinforcement learning (MADRL) has received
increasing research interest and has been widely applied to computer games and …

Multiagent Deep Reinforcement Learning Algorithms in StarCraft II: A Review

Y Li, Y Wang, Y Zhou - IEEE Access, 2024 - ieeexplore.ieee.org
StarCraft II, as a real-time strategy game, features multiagent collaboration, complex
decision-making processes, partially observable environments, and long-term credit …

Multi-agent Decision-making at Unsignalized Intersections with Reinforcement Learning from Demonstrations

C Huang, J Zhao, H Zhou, H Zhang… - 2023 IEEE Intelligent …, 2023 - ieeexplore.ieee.org
Intersections are key nodes and also bottlenecks of urban road networks, so improving the
traffic efficiency at intersections is beneficial to improving overall traffic throughput and …

Mcmarl: Parameterizing value function via mixture of categorical distributions for multi-agent reinforcement learning

J Zhao, M Yang, Y Zhao, X Hu… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
In cooperative multi-agent tasks, a team of agents jointly interact with an environment by
taking actions, receiving a team reward and observing the next state. During the interactions …

[PDF][PDF] Navigating Organization Dynamics: The Real-World Example of Condominium Life in Sicily During the COVID-19 Era in Late 2022-2023

R Fucà, S Cubico - International Journal, 2024 - researchgate.net
The COVID-19 pandemic brought unprecedented challenges, especially in shared living
environments. This study explores the behavior of 39 residents, aged 17 to 91, in a Sicilian …