S
Seyed Sajad Mousavi
Researcher at National University of Ireland
Publications - 4
Citations - 451
Seyed Sajad Mousavi is an academic researcher from National University of Ireland. The author has contributed to research in topics: Reinforcement learning & Artificial neural network. The author has an hindex of 3, co-authored 4 publications receiving 286 citations.
Papers
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Journal ArticleDOI
Traffic light control using deep policy-gradient and value-function-based reinforcement learning
TL;DR: In this paper, two kinds of RL algorithms, deep policy-gradient and value-function-based agents, are proposed to predict the best traffic signal for a traffic intersection in a traffic simulator.
Book ChapterDOI
Deep Reinforcement Learning: An Overview
TL;DR: This article reviewed the recent advances in deep reinforcement learning with focus on the most used deep architectures such as autoencoders, convolutional neural networks and recurrent neural networks which have successfully been combined with the reinforcement learning framework.
Book ChapterDOI
Deep Reinforcement Learning: An Overview
TL;DR: This article reviews the recent advances in deep reinforcement learning with focus on the most used deep architectures such as autoencoders, convolutional neural networks and recurrent neural networks which have successfully been come together with the reinforcement learning framework.
Posted Content
Traffic Light Control Using Deep Policy-Gradient and Value-Function Based Reinforcement Learning
TL;DR: In this article, a deep policy-gradient and value-function-based agent is proposed to predict the best traffic signal for a traffic intersection, based on a snapshot of the current state of a graphical traffic simulator.