activity
20162022
most citedA Review of Cooperative Multi-Agent Deep Reinforcement Learning

73 citations · 184 across the 6 of their papers we have counts for

collaborators

6 papers

physics.med-ph2022

Machine Learning to Generate Adjustable Dose Distributions in Head-and-Neck Cancer Radiation Therapy

Davood Hajinezhad, Afshin Oroojlooy, Mohammadreza Nazari +5

In this work, we propose a Machine Learning model that generates an adjustable 3D dose distribution for external beam radiation therapy for head-and-neck cancer treatments. In cont…

cs.LG2020★ 40 cited

AttendLight: Universal Attention-Based Reinforcement Learning Model for Traffic Signal Control

Afshin Oroojlooy, Mohammadreza Nazari, Davood Hajinezhad +1

We propose AttendLight, an end-to-end Reinforcement Learning (RL) algorithm for the problem of traffic signal control. Previous approaches for this problem have the shortcoming tha…

cs.LG2019★ 73 cited

A Review of Cooperative Multi-Agent Deep Reinforcement Learning

Afshin OroojlooyJadid, Davood Hajinezhad

Deep Reinforcement Learning has made significant progress in multi-agent systems in recent years. In this review article, we have focused on presenting recent approaches on Multi-A…

math.OC2019

Gradient-Free Multi-Agent Nonconvex Nonsmooth Optimization

Davood Hajinezhad, Michael Zavlanos

In this paper, we consider the problem of minimizing the sum of nonconvex and possibly nonsmooth functions over a connected multi-agent network, where the agents have partial knowl…

math.OC2017★ 37 cited

Zeroth Order Nonconvex Multi-Agent Optimization over Networks

Davood Hajinezhad, Mingyi Hong, Alfredo Garcia

In this paper, we consider distributed optimization problems over a multi-agent network, where each agent can only partially evaluate the objective function, and it is allowed to e…

math.OC2016★ 34 cited

NESTT: A Nonconvex Primal-Dual Splitting Method for Distributed and Stochastic Optimization

Davood Hajinezhad, Mingyi Hong, Tuo Zhao +1

We study a stochastic and distributed algorithm for nonconvex problems whose objective consists of a sum of nonconvex -smooth functions, plus a nonsmooth regularizer. Th…