Download or read book Particle Swarm Based Reinforcement Learning for Path Planning and Traffic Congestion written by Ashley Phan and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: In 2019, the average American commuter wasted approximately two and a half days due to traffic delays. Researchers suggest that these delays could be relieved by the addition of intelligent transportation systems, such as navigational systems that identify multiple high-speed travel routes or sophisticated traffic signals that can adapt to different traffic patterns. This dissertation explores the hybridization of the swarm intelligence algorithm, particle swarm optimization, with the reinforcement learning algorithm, Q-learning, and the hierarchical reinforcement learning algorithm,MAX-Q, to produce an intelligent path-planning algorithm and an adaptive traffic control system. By combining these algorithms with particle swarm optimization, the search space of a single agent is reduced through the parallelization and collaboration of multiple agents. Alternatively, the use of a look-up table improves the performance of particle swarm optimization by enhancing the swarm's ability to learn and balance the local and global search. In order to further improve the performance of the hybrid algorithms, a local particle swarm optimization variant was incorporated into the algorithms' action selection policies. This combination results in two hybrid intelligent optimization algorithms, Q-learning with Local Particle Swarm Optimization and MAXQ with Particle Swarm Optimization. When tasked with path planning in the Taxi World environment, QLPSO and MAXQPSO collectively learned the optimal policy in 46.44% fewer episodes than state-of-the-art algorithms and completed the task in 25.57% fewer steps. Given the success of the novel methods in the path planning problem, the two algorithms were slightly modified to identify the optimal policies for the traffic control problem. For various traffic networks, the algorithms collectively minimized the total wait time by an average of 16.31% and decreased the average wait time per vehicle by 11.43%. The combination of PSO and the learning algorithms demonstrate notable benefits as intelligent transportation systems.

Download or read book Multidimensional Particle Swarm Optimization for Machine Learning and Pattern Recognition written by Serkan Kiranyaz and published by Springer Science & Business Media. This book was released on 2013-07-16 with total page 343 pages. Available in PDF, EPUB and Kindle. Book excerpt: For many engineering problems we require optimization processes with dynamic adaptation as we aim to establish the dimension of the search space where the optimum solution resides and develop robust techniques to avoid the local optima usually associated with multimodal problems. This book explores multidimensional particle swarm optimization, a technique developed by the authors that addresses these requirements in a well-defined algorithmic approach. After an introduction to the key optimization techniques, the authors introduce their unified framework and demonstrate its advantages in challenging application domains, focusing on the state of the art of multidimensional extensions such as global convergence in particle swarm optimization, dynamic data clustering, evolutionary neural networks, biomedical applications and personalized ECG classification, content-based image classification and retrieval, and evolutionary feature synthesis. The content is characterized by strong practical considerations, and the book is supported with fully documented source code for all applications presented, as well as many sample datasets. The book will be of benefit to researchers and practitioners working in the areas of machine intelligence, signal processing, pattern recognition, and data mining, or using principles from these areas in their application domains. It may also be used as a reference text for graduate courses on swarm optimization, data clustering and classification, content-based multimedia search, and biomedical signal processing applications.

Download or read book Proceedings of 2021 International Conference on Autonomous Unmanned Systems ICAUS 2021 written by Meiping Wu and published by Springer Nature. This book was released on 2022-03-18 with total page 3575 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book includes original, peer-reviewed research papers from the ICAUS 2021, which offers a unique and interesting platform for scientists, engineers and practitioners throughout the world to present and share their most recent research and innovative ideas. The aim of the ICAUS 2021 is to stimulate researchers active in the areas pertinent to intelligent unmanned systems. The topics covered include but are not limited to Unmanned Aerial/Ground/Surface/Underwater Systems, Robotic, Autonomous Control/Navigation and Positioning/ Architecture, Energy and Task Planning and Effectiveness Evaluation Technologies, Artificial Intelligence Algorithm/Bionic Technology and Its Application in Unmanned Systems. The papers showcased here share the latest findings on Unmanned Systems, Robotics, Automation, Intelligent Systems, Control Systems, Integrated Networks, Modeling and Simulation. It makes the book a valuable asset for researchers, engineers, and university students alike.

Download or read book Optimizing Path Planning in 3D Environments with Reinforcement Learning and Sampling based Algorithms written by Wensi Huang and published by . This book was released on 2023 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Motion planning (also known as path planning) is a fundamental problem in the field of robotics and autonomous systems, where the objective is to find a collision-free path for an agent from a starting position to a goal state. Despite the importance of motion planning, comparing the performance of various algorithms under the same environment has been rarely explored. Furthermore, the lack of sufficient evaluation metrics in reinforcement learning (RL) studies can hinder the understanding of each algorithm's performance. This thesis investigates the problem of finding the optimal path in 3D environments using both sampling-based and RL algorithms. The study evaluates the performance of six algorithms, including Rapidly-exploring Random Trees (RRT), RRT*, Q-learning, Deep Q-Network (DQN), Trust Region Policy Optimization (TRPO), and Proximal Policy Optimization (PPO), while considering the impact of different features in complex 3D spaces. Simulation results indicate that RRT* outperforms other algorithms in completing a specific path planning task in a 3D grid map. The significance of this study lies in providing a comprehensive comparison of different path planning algorithms under the same environment and evaluating them using various metrics. This evaluation can serve as a useful guide for selecting an appropriate algorithm to solve specific motion planning problems.

Download or read book Artificial Intelligence and Soft Computing written by Amit Konar and published by CRC Press. This book was released on 2018-10-08 with total page 503 pages. Available in PDF, EPUB and Kindle. Book excerpt: With all the material available in the field of artificial intelligence (AI) and soft computing-texts, monographs, and journal articles-there remains a serious gap in the literature. Until now, there has been no comprehensive resource accessible to a broad audience yet containing a depth and breadth of information that enables the reader to fully understand and readily apply AI and soft computing concepts. Artificial Intelligence and Soft Computing fills this gap. It presents both the traditional and the modern aspects of AI and soft computing in a clear, insightful, and highly comprehensive style. It provides an in-depth analysis of mathematical models and algorithms and demonstrates their applications in real world problems. Beginning with the behavioral perspective of "human cognition," the text covers the tools and techniques required for its intelligent realization on machines. The author addresses the classical aspects-search, symbolic logic, planning, and machine learning-in detail and includes the latest research in these areas. He introduces the modern aspects of soft computing from first principles and discusses them in a manner that enables a beginner to grasp the subject. He also covers a number of other leading aspects of AI research, including nonmonotonic and spatio-temporal reasoning, knowledge acquisition, and much more. Artificial Intelligence and Soft Computing: Behavioral and Cognitive Modeling of the Human Brain is unique for its diverse content, clear presentation, and overall completeness. It provides a practical, detailed introduction that will prove valuable to computer science practitioners and students as well as to researchers migrating to the subject from other disciplines.

Download or read book Improving Particle Swarm Optimization Path Planning Through Inclusion of Flight Mechanics written by Joseph Scott Holub and published by . This book was released on 2010 with total page 104 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Search and Optimization by Metaheuristics written by Ke-Lin Du and published by Birkhäuser. This book was released on 2016-07-20 with total page 437 pages. Available in PDF, EPUB and Kindle. Book excerpt: This textbook provides a comprehensive introduction to nature-inspired metaheuristic methods for search and optimization, including the latest trends in evolutionary algorithms and other forms of natural computing. Over 100 different types of these methods are discussed in detail. The authors emphasize non-standard optimization problems and utilize a natural approach to the topic, moving from basic notions to more complex ones. An introductory chapter covers the necessary biological and mathematical backgrounds for understanding the main material. Subsequent chapters then explore almost all of the major metaheuristics for search and optimization created based on natural phenomena, including simulated annealing, recurrent neural networks, genetic algorithms and genetic programming, differential evolution, memetic algorithms, particle swarm optimization, artificial immune systems, ant colony optimization, tabu search and scatter search, bee and bacteria foraging algorithms, harmony search, biomolecular computing, quantum computing, and many others. General topics on dynamic, multimodal, constrained, and multiobjective optimizations are also described. Each chapter includes detailed flowcharts that illustrate specific algorithms and exercises that reinforce important topics. Introduced in the appendix are some benchmarks for the evaluation of metaheuristics. Search and Optimization by Metaheuristics is intended primarily as a textbook for graduate and advanced undergraduate students specializing in engineering and computer science. It will also serve as a valuable resource for scientists and researchers working in these areas, as well as those who are interested in search and optimization methods.

Download or read book Bioinspired Optimization Methods and Their Applications written by Peter Korošec and published by Springer. This book was released on 2018-05-11 with total page 345 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the thoroughly refereed revised selected papers of the 10th International Conference on Bioinspired Optimization Models and Their Applications, BIOMA 2018, held in Paris, France, in May 2018. The 27 revised full papers were selected from 53 submissions and present papers in all aspects of bioinspired optimization research such as new algorithmic developments, high-impact applications, new research challenges, theoretical contributions, implementation issues, and experimental studies.

Download or read book Particle Swarm Optimization and Intelligence Advances and Applications written by Parsopoulos, Konstantinos E. and published by IGI Global. This book was released on 2010-01-31 with total page 328 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This book presents the most recent and established developments of Particle swarm optimization (PSO) within a unified framework by noted researchers in the field"--Provided by publisher.

Download or read book Pan African Artificial Intelligence and Smart Systems written by Telex Magloire Ngatched Nkouatchah and published by Springer Nature. This book was released on 2023-02-20 with total page 441 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed post-conference proceedings of the Second International Conference on Pan-African Intelligence and Smart Systems, PAAISS 2022, which was held in Dakar, Senegal, in November 2022. The 27 revised full papers presented were carefully selected from 70 submissions. The theme of PAAISS 2022 was: ​IoT and Enabling Smart System Technologies, Special Topics of African Interest, Artificial Intelligence Theory and Methods, Artificial Intelligence Applications in Medicine, Remote sensing and AI in Agriculture, AI applications and Smart Systems technologies, Affective Computing, Intelligent Transportation systems.

Download or read book Principles of Robot Motion written by Howie Choset and published by MIT Press. This book was released on 2005-05-20 with total page 642 pages. Available in PDF, EPUB and Kindle. Book excerpt: A text that makes the mathematical underpinnings of robot motion accessible and relates low-level details of implementation to high-level algorithmic concepts. Robot motion planning has become a major focus of robotics. Research findings can be applied not only to robotics but to planning routes on circuit boards, directing digital actors in computer graphics, robot-assisted surgery and medicine, and in novel areas such as drug design and protein folding. This text reflects the great advances that have taken place in the last ten years, including sensor-based planning, probabalistic planning, localization and mapping, and motion planning for dynamic and nonholonomic systems. Its presentation makes the mathematical underpinnings of robot motion accessible to students of computer science and engineering, rleating low-level implementation details to high-level algorithmic concepts.

Download or read book Robotic Systems Concepts Methodologies Tools and Applications written by Management Association, Information Resources and published by IGI Global. This book was released on 2020-01-03 with total page 2075 pages. Available in PDF, EPUB and Kindle. Book excerpt: Through expanded intelligence, the use of robotics has fundamentally transformed a variety of fields, including manufacturing, aerospace, medicine, social services, and agriculture. Continued research on robotic design is critical to solving various dynamic obstacles individuals, enterprises, and humanity at large face on a daily basis. Robotic Systems: Concepts, Methodologies, Tools, and Applications is a vital reference source that delves into the current issues, methodologies, and trends relating to advanced robotic technology in the modern world. Highlighting a range of topics such as mechatronics, cybernetics, and human-computer interaction, this multi-volume book is ideally designed for robotics engineers, mechanical engineers, robotics technicians, operators, software engineers, designers, programmers, industry professionals, researchers, students, academicians, and computer practitioners seeking current research on developing innovative ideas for intelligent and autonomous robotics systems.

Download or read book Reinforcement Learning written by Marco Wiering and published by Springer Science & Business Media. This book was released on 2012-03-05 with total page 653 pages. Available in PDF, EPUB and Kindle. Book excerpt: Reinforcement learning encompasses both a science of adaptive behavior of rational beings in uncertain environments and a computational methodology for finding optimal behaviors for challenging problems in control, optimization and adaptive behavior of intelligent agents. As a field, reinforcement learning has progressed tremendously in the past decade. The main goal of this book is to present an up-to-date series of survey articles on the main contemporary sub-fields of reinforcement learning. This includes surveys on partially observable environments, hierarchical task decompositions, relational knowledge representation and predictive state representations. Furthermore, topics such as transfer, evolutionary methods and continuous spaces in reinforcement learning are surveyed. In addition, several chapters review reinforcement learning methods in robotics, in games, and in computational neuroscience. In total seventeen different subfields are presented by mostly young experts in those areas, and together they truly represent a state-of-the-art of current reinforcement learning research. Marco Wiering works at the artificial intelligence department of the University of Groningen in the Netherlands. He has published extensively on various reinforcement learning topics. Martijn van Otterlo works in the cognitive artificial intelligence group at the Radboud University Nijmegen in The Netherlands. He has mainly focused on expressive knowledge representation in reinforcement learning settings.

Download or read book Decision Making Techniques for Autonomous Vehicles written by Jorge Villagra and published by Elsevier. This book was released on 2023-03-03 with total page 426 pages. Available in PDF, EPUB and Kindle. Book excerpt: Decision-Making Techniques for Autonomous Vehicles provides a general overview of control and decision-making tools that could be used in autonomous vehicles. Motion prediction and planning tools are presented, along with the use of machine learning and adaptability to improve performance of algorithms in real scenarios. The book then examines how driver monitoring and behavior analysis are used produce comprehensive and predictable reactions in automated vehicles. The book ultimately covers regulatory and ethical issues to consider for implementing correct and robust decision-making. This book is for researchers as well as Masters and PhD students working with autonomous vehicles and decision algorithms. Provides a complete overview of decision-making and control techniques for autonomous vehicles Includes technical, physical, and mathematical explanations to provide knowledge for implementation of tools Features machine learning to improve performance of decision-making algorithms Shows how regulations and ethics influence the development and implementation of these algorithms in real scenarios

Download or read book Meta Heuristics written by Stefan Voß and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 513 pages. Available in PDF, EPUB and Kindle. Book excerpt: Meta-Heuristics: Advances and Trends in Local Search Paradigms for Optimizations comprises a carefully refereed selection of extended versions of the best papers presented at the Second Meta-Heuristics Conference (MIC 97). The selected articles describe the most recent developments in theory and applications of meta-heuristics, heuristics for specific problems, and comparative case studies. The book is divided into six parts, grouped mainly by the techniques considered. The extensive first part with twelve papers covers tabu search and its application to a great variety of well-known combinatorial optimization problems (including the resource-constrained project scheduling problem and vehicle routing problems). In the second part we find one paper where tabu search and simulated annealing are investigated comparatively and two papers which consider hybrid methods combining tabu search with genetic algorithms. The third part has four papers on genetic and evolutionary algorithms. Part four arrives at a new paradigm within meta-heuristics. The fifth part studies the behavior of parallel local search algorithms mainly from a tabu search perspective. The final part examines a great variety of additional meta-heuristics topics, including neural networks and variable neighbourhood search as well as guided local search. Furthermore, the integration of meta-heuristics with the branch-and-bound paradigm is investigated.

Download or read book Advances in Smart Vehicular Technology Transportation Communication and Applications written by Shaoquan Ni and published by Springer Nature. This book was released on 2023-05-14 with total page 578 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book includes selected papers from the fifth International Conference on Smart Vehicular Technology, Transportation, Communication and Applications (VTCA 2022), held in online mode during December 24–26, 2022. The book includes research works from engineers, researchers, and practitioners interested in the advances and applications in the field of vehicle technology and communication. The book covers four tracks, namely (1) vehicular networking security, (2) vehicular electronics, (3) intelligent transportation systems and applications, and (4) smart vehicular communication networks and telematics.

Download or read book Risk Detection and Cyber Security for the Success of Contemporary Computing written by Kumar, Raghvendra and published by IGI Global. This book was released on 2023-11-09 with total page 502 pages. Available in PDF, EPUB and Kindle. Book excerpt: With the rapid evolution of technology, identifying new risks is a constantly moving target. The metaverse is a virtual space that is interconnected with cloud computing and with companies, organizations, and even countries investing in virtual real estate. The questions of what new risks will become evident in these virtual worlds and in augmented reality and what real-world impacts they will have in an ever-expanding internet of things (IoT) need to be answered. Within continually connected societies that require uninterrupted functionality, cyber security is vital, and the ability to detect potential risks and ensure the security of computing systems is crucial to their effective use and success. Proper utilization of the latest technological advancements can help in developing more efficient techniques to prevent cyber threats and enhance cybersecurity. Risk Detection and Cyber Security for the Success of Contemporary Computing presents the newest findings with technological advances that can be utilized for more effective prevention techniques to protect against cyber threats. This book is led by editors of best-selling and highly indexed publications, and together they have over two decades of experience in computer science and engineering. Featuring extensive coverage on authentication techniques, cloud security, and mobile robotics, this book is ideally designed for students, researchers, scientists, and engineers seeking current research on methods, models, and implementation of optimized security in digital contexts.