Data-Driven Structured Policy Iteration for Homogeneous Distributed Systems

1 code implementation • 22 Mar 2021 • Siavash Alemzadeh, Shahriar Talebi, Mehran Mesbahi

Control of networked systems, comprised of interacting agents, is often achieved through modeling the underlying interactions.

Adaptive Traffic Control with Deep Reinforcement Learning:Towards State-of-the-art and Beyond

1 code implementation • 21 Jul 2020 • Siavash Alemzadeh, Ramin Moslemi, Ratnesh Sharma, Mehran Mesbahi

In this work, we study adaptive data-guided traffic planning and control using Reinforcement Learning (RL).

Decision Making reinforcement-learning +1

Deep Learning-based Resource Allocation for Infrastructure Resilience

1 code implementation • 12 Jul 2020 • Siavash Alemzadeh, Hesam Talebiyan, Shahriar Talebi, Leonardo Duenas-Osorio, Mehran Mesbahi

From an optimization point of view, resource allocation is one of the cornerstones of research for addressing limiting factors commonly arising in applications such as power outages and traffic jams.

On Regularizability and its Application to Online Control of Unstable LTI Systems

1 code implementation • 29 May 2020 • Shahriar Talebi, Siavash Alemzadeh, Niyousha Rahimi, Mehran Mesbahi

Learning, say through direct policy updates, often requires assumptions such as knowing a priori that the initial policy (gain) is stabilizing, or persistently exciting (PE) input-output data, is available.

Time Series Analysis