Proximal Policy Optimization Based Decentralized Networked Multi-Agent Reinforcement Learning
J Liu, F Li, J Wang, H Han - 2024 IEEE 18th International …, 2024 - ieeexplore.ieee.org
Networked multi-agent reinforcement learning (NMARL) is widely used in multi-agent
systems (MASs). However, most existing NMARL algorithms share the global state and …
systems (MASs). However, most existing NMARL algorithms share the global state and …
A Distributed Primal-Dual Method for Constrained Multi-agent Reinforcement Learning with General Parameterization
A Kahe, H Kebriaei - arXiv preprint arXiv:2410.15335, 2024 - arxiv.org
This paper proposes a novel distributed approach for solving a cooperative Constrained
Multi-agent Reinforcement Learning (CMARL) problem, where agents seek to minimize a …
Multi-agent Reinforcement Learning (CMARL) problem, where agents seek to minimize a …
Elevating AI Research at Cognitive Agents and Interaction Lab: A Technical Report on High-Performance Computing Infrastructure
MM Khan - Authorea Preprints, 2023 - techrxiv.org
The Cognitive Agents and Interaction Lab (CAIL) at the University of Dhaka has strategically
developed a focused High-Performance Computing (HPC) facility, underpinning its niche in …
developed a focused High-Performance Computing (HPC) facility, underpinning its niche in …