Multi-agent Reinforcement Learning for Integrated Network of Adaptive Traffic Signal Controllers (MARLIN-ATSC).

Multi-agent Reinforcement Learning for Integrated Network of Adaptive Traffic Signal Controllers (MARLIN-ATSC). PDF Author: Samah El-Tantawy
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Category :
Languages : en
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Multi-agent Reinforcement Learning for Integrated Network of Adaptive Traffic Signal Controllers (MARLIN-ATSC).

Multi-agent Reinforcement Learning for Integrated Network of Adaptive Traffic Signal Controllers (MARLIN-ATSC). PDF Author: Samah El-Tantawy
Publisher:
ISBN:
Category :
Languages : en
Pages :

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Data-driven Adaptive Traffic Signal Control Via Deep Reinforcement Learning

Data-driven Adaptive Traffic Signal Control Via Deep Reinforcement Learning PDF Author: Tian Tan
Publisher:
ISBN:
Category :
Languages : en
Pages :

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Book Description
Adaptive traffic signal control (ATSC) system serves a significant role for relieving urban traffic congestion. The system is capable of adjusting signal phases and timings of all traffic lights simultaneously according to real-time traffic sensor data, resulting in a better overall traffic management and an improved traffic condition on road. In recent years, deep reinforcement learning (DRL), one powerful paradigm in artificial intelligence (AI) for sequential decision-making, has drawn great attention from transportation researchers. The following three properties of DRL make it very attractive and ideal for the next generation ATSC system: (1) model-free: DRL reasons about the optimal control strategies directly from data without making additional assumptions on the underlying traffic distributions and traffic flows. Compared with traditional traffic optimization methods, DRL avoids the cumbersome formulation of traffic dynamics and modeling; (2) self-learning: DRL self-learns the signal control knowledge from traffic data with minimal human expertise; (3) simple data requirement: by using large nonlinear neural networks as function approximators, DRL has enough representation power to map directly from simple traffic measurements, e.g. queue length and waiting time, to signal control policies. This thesis focuses on building data-driven and adaptive controllers via deep reinforcement learning for large-scale traffic signal control systems. In particular, the thesis first proposes a hierarchical decentralized-to-centralized DRL framework for large-scale ATSC to better coordinate multiple signalized intersections in the traffic system. Second, the thesis introduces efficient DRL with efficient exploration for ATSC to greatly improve sample complexity of DRL algorithms, making them more suitable for real-world control systems. Furthermore, the thesis combines multi-agent system with efficient DRL to solve large-scale ATSC problems that have multiple intersections. Finally, the thesis presents several algorithmic extensions to handle complex topology and heterogeneous intersections in real-world traffic networks. To gauge the performance of the presented DRL algorithms, various experiments have been conducted and included in the thesis both on small-scale and on large-scale simulated traffic networks. The empirical results have demonstrated that the proposed DRL algorithms outperform both rule-based control policy and commonly-used off-the-shelf DRL algorithms by a significant margin. Moreover, the proposed efficient MARL algorithms have achieved the state-of-the-art performance with improved sample-complexity for large-scale ATSC.

Autonomic Road Transport Support Systems

Autonomic Road Transport Support Systems PDF Author: Thomas Leo McCluskey
Publisher: Birkhäuser
ISBN: 3319258087
Category : Computers
Languages : en
Pages : 303

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Book Description
The work on Autonomic Road Transport Support (ARTS) presented here aims at meeting the challenge of engineering autonomic behavior in Intelligent Transportation Systems (ITS) by fusing research from the disciplines of traffic engineering and autonomic computing. Ideas and techniques from leading edge artificial intelligence research have been adapted for ITS over the last 30 years. Examples include adaptive control embedded in real time traffic control systems, heuristic algorithms (e.g. in SAT-NAV systems), image processing and computer vision (e.g. in automated surveillance interpretation). Autonomic computing which is inspired from the biological example of the body’s autonomic nervous system is a more recent development. It allows for a more efficient management of heterogeneous distributed computing systems. In the area of computing, autonomic systems are endowed with a number of properties that are generally referred to as self-X properties, including self-configuration, self-healing, self-optimization, self-protection and more generally self-management. Some isolated examples of autonomic properties such as self-adaptation have found their way into ITS technology and have already proved beneficial. This edited volume provides a comprehensive introduction to Autonomic Road Transport Support (ARTS) and describes the development of ARTS systems. It starts out with the visions, opportunities and challenges, then presents the foundations of ARTS and the platforms and methods used and it closes with experiences from real-world applications and prototypes of emerging applications. This makes it suitable for researchers and practitioners in the fields of autonomic computing, traffic and transport management and engineering, AI, and software engineering. Graduate students will benefit from state-of-the-art description, the study of novel methods and the case studies provided.

Applications of Intelligent Systems

Applications of Intelligent Systems PDF Author: N. Petkov
Publisher: IOS Press
ISBN: 1614999295
Category : Computers
Languages : en
Pages : 370

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Book Description
The deployment of intelligent systems to tackle complex processes is now commonplace in many fields from medicine and agriculture to industry and tourism. This book presents scientific contributions from the 1st International Conference on Applications of Intelligent Systems (APPIS 2018) held at the Museo Elder in Las Palmas de Gran Canaria, Spain, from 10 to 12 January 2018. The aim of APPIS 2018 was to bring together scientists working on the development of intelligent computer systems and methods for machine learning, artificial intelligence, pattern recognition, and related techniques with an emphasis on their application to various problems. The 34 peer-reviewed papers included here cover an extraordinarily wide variety of topics – everything from semi-supervised learning to matching electro-chemical sensor information with human odor perception – but what they all have in common is the design and application of intelligent systems and their role in tackling diverse and complex challenges. The book will be of particular interest to all those involved in the development and application of intelligent systems.

Algorithms and Architectures for Parallel Processing

Algorithms and Architectures for Parallel Processing PDF Author: Shadi Ibrahim
Publisher: Springer
ISBN: 3319654829
Category : Computers
Languages : en
Pages : 836

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Book Description
This book constitutes the proceedings of the 17th International Conference on Algorithms and Architectures for Parallel Processing, ICA3PP 2017, held in Helsinki, Finland, in August 2017. The 25 full papers presented were carefully reviewed and selected from 117 submissions. They cover topics such as parallel and distributed architectures; software systems and programming models; distributed and network-based computing; big data and its applications; parallel and distributed algorithms; applications of parallel and distributed computing; service dependability and security in distributed and parallel systems; service dependability and security in distributed and parallel systems; performance modeling and evaluation.This volume also includes 41 papers of four workshops, namely: the 4th International Workshop on Data, Text, Web, and Social Network Mining (DTWSM 2017), the 5th International Workshop on Parallelism in Bioinformatics (PBio 2017), the First International Workshop on Distributed Autonomous Computing in Smart City (DACSC 2017), and the Second International Workshop on Ultrascale Computing for Early Researchers (UCER 2017).

Distributed Computer and Communication Networks

Distributed Computer and Communication Networks PDF Author: Vladimir M. Vishnevskiy
Publisher: Springer Nature
ISBN: 3031618351
Category :
Languages : en
Pages : 124

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Book Description


Handbook on Artificial Intelligence and Transport

Handbook on Artificial Intelligence and Transport PDF Author: Hussein Dia
Publisher: Edward Elgar Publishing
ISBN: 1803929545
Category : Computers
Languages : en
Pages : 649

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Book Description
With AI advancements eliciting imminent changes to our transport systems, this enlightening Handbook presents essential research on this evolution of the transportation sector. It focuses on not only urban planning, but relevant themes in law and ethics to form a unified resource on the practicality of AI use.

Computer Supported Cooperative Work and Social Computing

Computer Supported Cooperative Work and Social Computing PDF Author: Yuqing Sun
Publisher: Springer Nature
ISBN: 9819996406
Category : Computers
Languages : en
Pages : 566

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Book Description
This two-volume set constitutes the revised selected papers of the 18th CCF Conference on Computer Supported Cooperative Work and Social Computing, ChineseCSCW 2023 held in Harbin, China, in August 2023. The 54 full papers and 28 short papers presented in these proceedings were carefully reviewed and selected from 221 submissions. The papers are organized in the following topical sections: Social Media and Online Communities; Collaborative Mechanisms, Models, Approaches, Algorithms and Systems; Crowd Intelligence and Crowd Cooperative Computing; Cooperative Evolutionary Computation and Human-like Intelligent Collaboration; Domain-Specific Collaborative Applications.

Advances in Computing and Network Communications

Advances in Computing and Network Communications PDF Author: Sabu M. Thampi
Publisher: Springer Nature
ISBN: 9813369779
Category : Technology & Engineering
Languages : en
Pages : 705

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Book Description
This book constitutes the thoroughly refereed post-conference proceedings of the 4th International Conference on Computing and Network Communications (CoCoNet'20), October 14–17, 2020, Chennai, India. The papers presented were carefully reviewed and selected from several initial submissions. The papers are organized in topical sections on Signal, Image and Speech Processing, Wireless and Mobile Communication, Internet of Things, Cloud and Edge Computing, Distributed Systems, Machine Intelligence, Data Analytics, Cybersecurity, Artificial Intelligence and Cognitive Computing and Circuits and Systems. The book is directed to the researchers and scientists engaged in various fields of computing and network communication domains.

Algorithms and Architectures for Parallel Processing

Algorithms and Architectures for Parallel Processing PDF Author: Guojun Wang
Publisher: Springer
ISBN: 3319271377
Category : Computers
Languages : en
Pages : 844

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Book Description
This four volume set LNCS 9528, 9529, 9530 and 9531 constitutes the refereed proceedings of the 15th International Conference on Algorithms and Architectures for Parallel Processing, ICA3PP 2015, held in Zhangjiajie, China, in November 2015. The 219 revised full papers presented together with 77 workshop papers in these four volumes were carefully reviewed and selected from 807 submissions (602 full papers and 205 workshop papers). The first volume comprises the following topics: parallel and distributed architectures; distributed and network-based computing and internet of things and cyber-physical-social computing. The second volume comprises topics such as big data and its applications and parallel and distributed algorithms. The topics of the third volume are: applications of parallel and distributed computing and service dependability and security in distributed and parallel systems. The covered topics of the fourth volume are: software systems and programming models and performance modeling and evaluation.