PROMPT: Learning Dynamic Resource Allocation Policies for Network Applications

no code implementations • 19 Jan 2022 • Drew Penney, Bin Li, Jaroslaw Sydir, Lizhong Chen, Charlie Tai, Stefan Lee, Eoin Walsh, Thomas Long

A growing number of service providers are exploring methods to improve server utilization and reduce power consumption by co-scheduling high-priority latency-critical workloads with best-effort workloads.

Scheduling

Resource Management in Wireless Networks via Multi-Agent Deep Reinforcement Learning

no code implementations • 14 Feb 2020 • Navid Naderializadeh, Jaroslaw Sydir, Meryem Simsek, Hosein Nikopour

We propose a mechanism for distributed resource management and interference mitigation in wireless networks using multi-agent deep reinforcement learning (RL).

Management reinforcement-learning +2

When Multiple Agents Learn to Schedule: A Distributed Radio Resource Management Framework

no code implementations • 20 Jun 2019 • Navid Naderializadeh, Jaroslaw Sydir, Meryem Simsek, Hosein Nikopour, Shilpa Talwar

Interference among concurrent transmissions in a wireless network is a key factor limiting the system performance.

Management Reinforcement Learning (RL) +1