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Algorithms and Autonomy by Alan Rubel,Clinton Castro,Adam Pham Pdf
This book examines how algorithms in criminal justice, education, housing, elections and beyond affect autonomy, freedom, and democracy. This title is also available as Open Access on Cambridge Core.
Autonomous Search by Youssef Hamadi,Eric Monfroy,Frédéric Saubion Pdf
Decades of innovations in combinatorial problem solving have produced better and more complex algorithms. These new methods are better since they can solve larger problems and address new application domains. They are also more complex which means that they are hard to reproduce and often harder to fine-tune to the peculiarities of a given problem. This last point has created a paradox where efficient tools are out of reach of practitioners. Autonomous search (AS) represents a new research field defined to precisely address the above challenge. Its major strength and originality consist in the fact that problem solvers can now perform self-improvement operations based on analysis of the performances of the solving process -- including short-term reactive reconfiguration and long-term improvement through self-analysis of the performance, offline tuning and online control, and adaptive control and supervised control. Autonomous search "crosses the chasm" and provides engineers and practitioners with systems that are able to autonomously self-tune their performance while effectively solving problems. This is the first book dedicated to this topic, and it can be used as a reference for researchers, engineers, and postgraduates in the areas of constraint programming, machine learning, evolutionary computing, and feedback control theory. After the editors' introduction to autonomous search, the chapters are focused on tuning algorithm parameters, autonomous complete (tree-based) constraint solvers, autonomous control in metaheuristics and heuristics, and future autonomous solving paradigms. Autonomous search (AS) represents a new research field defined to precisely address the above challenge. Its major strength and originality consist in the fact that problem solvers can now perform self-improvement operations based on analysis of the performances of the solving process -- including short-term reactive reconfiguration and long-term improvement through self-analysis of the performance, offline tuning and online control, and adaptive control and supervised control. Autonomous search "crosses the chasm" and provides engineers and practitioners with systems that are able to autonomously self-tune their performance while effectively solving problems. This is the first book dedicated to this topic, and it can be used as a reference for researchers, engineers, and postgraduates in the areas of constraint programming, machine learning, evolutionary computing, and feedback control theory. After the editors' introduction to autonomous search, the chapters are focused on tuning algorithm parameters, autonomous complete (tree-based) constraint solvers, autonomous control in metaheuristics and heuristics, and future autonomous solving paradigms. This is the first book dedicated to this topic, and it can be used as a reference for researchers, engineers, and postgraduates in the areas of constraint programming, machine learning, evolutionary computing, and feedback control theory. After the editors' introduction to autonomous search, the chapters are focused on tuning algorithm parameters, autonomous complete (tree-based) constraint solvers, autonomous control in metaheuristics and heuristics, and future autonomous solving paradigms. This is the first book dedicated to this topic, and it can be used as a reference for researchers, engineers, and postgraduates in the areas of constraint programming, machine learning, evolutionary computing, and feedback control theory. After the editors' introduction to autonomous search, the chapters are focused on tuning algorithm parameters, autonomous complete (tree-based) constraint solvers, autonomous control in metaheuristics and heuristics, and future autonomous solving paradigms.
Autonomy and Unmanned Vehicles by Somaiyeh MahmoudZadeh,David M.W. Powers,Reza Bairam Zadeh Pdf
This book addresses higher–lower level decision autonomy for autonomous vehicles, and discusses the addition of a novel architecture to cover both levels. The proposed framework’s performance and stability are subsequently investigated by employing different meta-heuristic algorithms. The performance of the proposed architecture is shown to be largely independent of the algorithms employed; the use of diverse algorithms (subjected to the real-time performance of the algorithm) does not negatively affect the system’s real-time performance. By analyzing the simulation results, the book demonstrates that the proposed model provides perfect mission timing and task management, while also guaranteeing secure deployment. Although mainly intended as a research work, the book’s review chapters and the new approaches developed here are also suitable for use in courses for advanced undergraduate or graduate students.
Development and Testing of Navigation Algorithms for Autonomous Underwater Vehicles by Francesco Fanelli Pdf
This book focuses on pose estimation algorithms for Autonomous Underwater Vehicles (AUVs). After introducing readers to the state of the art, it describes a joint endeavor involving attitude and position estimation, and details the development of a nonlinear attitude observer that employs inertial and magnetic field data and is suitable for underwater use. In turn, it shows how the estimated attitude constitutes an essential type of input for UKF-based position estimators that combine position, depth, and velocity measurements. The book discusses the possibility of including real-time estimates of sea currents in the developed estimators, and highlights simulations that combine real-world navigation data and experimental test campaigns to evaluate the performance of the resulting solutions. In addition to proposing novel algorithms for estimating the attitudes and positions of AUVs using low-cost sensors and taking into account magnetic disturbances and ocean currents, the book provides readers with extensive information and a source of inspiration for the further development and testing of navigation algorithms for AUVs.
Foundations of Trusted Autonomy by Hussein A. Abbass,Jason Scholz,Darryn J. Reid Pdf
This book establishes the foundations needed to realize the ultimate goals for artificial intelligence, such as autonomy and trustworthiness. Aimed at scientists, researchers, technologists, practitioners, and students, it brings together contributions offering the basics, the challenges and the state-of-the-art on trusted autonomous systems in a single volume. The book is structured in three parts, with chapters written by eminent researchers and outstanding practitioners and users in the field. The first part covers foundational artificial intelligence technologies, while the second part covers philosophical, practical and technological perspectives on trust. Lastly, the third part presents advanced topics necessary to create future trusted autonomous systems. The book augments theory with real-world applications including cyber security, defence and space.
Introduction to Autonomous Robots by Nikolaus Correll Pdf
This book introduces concepts in mobile, autonomous robotics to 3rd-4th year students in Computer Science or a related discipline. The book covers principles of robot motion, forward and inverse kinematics of robotic arms and simple wheeled platforms, perception, error propagation, localization and simultaneous localization and mapping. The cover picture shows a wind-up toy that is smart enough to not fall off a table just using intelligent mechanism design and illustrate the importance of the mechanism in designing intelligent, autonomous systems. This book is open source, open to contributions, and released under a creative common license.
Ethics for Robots describes and defends a method for designing and evaluating ethics algorithms for autonomous machines, such as self-driving cars and search and rescue drones. Derek Leben argues that such algorithms should be evaluated by how effectively they accomplish the problem of cooperation among self-interested organisms, and therefore, rather than simulating the psychological systems that have evolved to solve this problem, engineers should be tackling the problem itself, taking relevant lessons from our moral psychology. Leben draws on the moral theory of John Rawls, arguing that normative moral theories are attempts to develop optimal solutions to the problem of cooperation. He claims that Rawlsian Contractarianism leads to the ‘Maximin’ principle – the action that maximizes the minimum value – and that the Maximin principle is the most effective solution to the problem of cooperation. He contrasts the Maximin principle with other principles and shows how they can often produce non-cooperative results. Using real-world examples – such as an autonomous vehicle facing a situation where every action results in harm, home care machines, and autonomous weapons systems – Leben contrasts Rawlsian algorithms with alternatives derived from utilitarianism and natural rights libertarianism. Including chapter summaries and a glossary of technical terms, Ethics for Robots is essential reading for philosophers, engineers, computer scientists, and cognitive scientists working on the problem of ethics for autonomous systems.
Toward a Practice of Autonomous Systems by Francisco J. Varela,Paul Bourgine Pdf
Artificial life embodies a recent and important conceptual step in modem science: asserting that the core of intelligence and cognitive abilities is the same as the capacity for living. The recent surge of interest in artificial life has pushed a whole range of engineering traditions, such as control theory and robotics, beyond classical notions of goal and planning into biologically inspired notions of viability and adaptation, situatedness and operational closure. These proceedings serve two important functions: they address bottom-up theories of artificial intelligence and explore what can be learned from simple models such as insects about the cognitive processes and characteristic autonomy of living organisms, while also engaging researchers and philosophers in an exciting examination of the epistemological basis of this new trend. Topics Artificial Animals • Genetic Algorithms • Autonomous Systems • Emergent Behaviors • Artificial Ecologies • Immunologic Algorithms • Self-Adapting Systems • Emergent Structures • Emotion And Motivation • Neural Networks • Coevolution • Fitness Landscapes Contributors H. Bersini, Domenico Parisi, Rodney A. Brooks, Christopher G. Langton, S. Kauffman, J.-L. Denenbourg, Pattie Maes, John Holland, T. Smithersm H. Swefel, H. Muhlenbein
Cybernetics and Algorithms in Intelligent Systems by Radek Silhavy Pdf
This book presents new approaches and methods applied to real-world problems, and in particular, exploratory research relating to novel approaches in the field of cybernetics and automation control theory. Particularly focusing on modern trends in selected fields of interest, it presents new algorithms and methods in intelligent systems in cybernetics. This book constitutes the third volume of the refereed proceedings of the Cybernetics and Algorithms in Intelligent Systems Section of the 7th Computer Science On-line Conference 2018 (CSOC 2018), held online in April 2018.
Toward a Practice of Autonomous Systems by Francisco J. Varela,Paul Bourgine Pdf
Artificial life embodies a recent and important conceptual step in modem science: asserting that the core of intelligence and cognitive abilities is the same as the capacity for living. The recent surge of interest in artificial life has pushed a whole range of engineering traditions, such as control theory and robotics, beyond classical notions of goal and planning into biologically inspired notions of viability and adaptation, situatedness and operational closure. These proceedings serve two important functions: they address bottom-up theories of artificial intelligence and explore what can be learned from simple models such as insects about the cognitive processes and characteristic autonomy of living organisms, while also engaging researchers and philosophers in an exciting examination of the epistemological basis of this new trend. Topics Artificial Animals • Genetic Algorithms • Autonomous Systems • Emergent Behaviors • Artificial Ecologies • Immunologic Algorithms • Self-Adapting Systems • Emergent Structures • Emotion And Motivation • Neural Networks • Coevolution • Fitness Landscapes Contributors H. Bersini, Domenico Parisi, Rodney A. Brooks, Christopher G. Langton, S. Kauffman, J.-L. Denenbourg, Pattie Maes, John Holland, T. Smithersm H. Swefel, H. Muhlenbein
Autonomous driving algorithms and Its IC Design by Jianfeng Ren,Dong Xia Pdf
With the rapid development of artificial intelligence and the emergence of various new sensors, autonomous driving has grown in popularity in recent years. The implementation of autonomous driving requires new sources of sensory data, such as cameras, radars, and lidars, and the algorithm processing requires a high degree of parallel computing. In this regard, traditional CPUs have insufficient computing power, while DSPs are good at image processing but lack sufficient performance for deep learning. Although GPUs are good at training, they are too “power-hungry,” which can affect vehicle performance. Therefore, this book looks to the future, arguing that custom ASICs are bound to become mainstream. With the goal of ICs design for autonomous driving, this book discusses the theory and engineering practice of designing future-oriented autonomous driving SoC chips. The content is divided into thirteen chapters, the first chapter mainly introduces readers to the current challenges and research directions in autonomous driving. Chapters 2–6 focus on algorithm design for perception and planning control. Chapters 7–10 address the optimization of deep learning models and the design of deep learning chips, while Chapters 11-12 cover automatic driving software architecture design. Chapter 13 discusses the 5G application on autonomous drving. This book is suitable for all undergraduates, graduate students, and engineering technicians who are interested in autonomous driving.
Intelligent Autonomy of UAVs by Yasmina Bestaoui Sebbane Pdf
Intelligent Autonomy of UAVs: Advanced Missions and Future Use provides an approach to the formulation of the fundamental task typical to any mission and provides guidelines of how this task can be solved by different generic robotic problems. As such, this book aims to provide a systems engineering approach to UAV projects, discovering the real problems that need to be resolved independently of the application. After an introduction to the rapidly evolving field of aerial robotics, the book presents topics such as autonomy, mission analysis, human-UAV teams, homogeneous and heterogeneous UAV teams, and finally, UAV-UGV teams. It then covers generic robotic problems such as orienteering and coverage. The book next introduces deployment, patrolling, and foraging, while the last part of the book tackles an important application: aerial search, tracking, and surveillance. This book is meant for both scientists and practitioners. For practitioners, it presents existing solutions that are categorized according to various missions: surveillance and reconnaissance, 3D mapping, urban monitoring, precision agriculture, forestry, disaster assessment and monitoring, security, industrial plant inspection, etc. For scientists, it provides an overview of generic robotic problems such as coverage and orienteering; deployment, patrolling and foraging; search, tracking, and surveillance. The design and analysis of algorithms raise a unique combination of questions from many fields, including robotics, operational research, control theory, and computer science.
Algorithms, Automation, and News by Neil Thurman,Seth C. Lewis,Jessica Kunert Pdf
This book examines the growing importance of algorithms and automation—including emerging forms of artificial intelligence—in the gathering, composition, and distribution of news. In it the authors connect a long line of research on journalism and computation with scholarly and professional terrain yet to be explored. Taken as a whole, these chapters share some of the noble ambitions of the pioneering publications on ‘reporting algorithms’, such as a desire to see computing help journalists in their watchdog role by holding power to account. However, they also go further, firstly by addressing the fuller range of technologies that computational journalism now consists of: from chatbots and recommender systems to artificial intelligence and atomised journalism. Secondly, they advance the literature by demonstrating the increased variety of uses for these technologies, including engaging underserved audiences, selling subscriptions, and recombining and re-using content. Thirdly, they problematise computational journalism by, for example, pointing out some of the challenges inherent in applying artificial intelligence to investigative journalism and in trying to preserve public service values. Fourthly, they offer suggestions for future research and practice, including by presenting a framework for developing democratic news recommenders and another that may help us think about computational journalism in a more integrated, structured manner. The chapters in this book were originally published as a special issue of Digital Journalism.
Autonomy for Marine Robots provides a timely and insightful overview of intelligent autonomy in marine robots. A brief history of this emerging field is provided, along with a discussion of the challenges unique to the underwater environment and their impact on the level of intelligent autonomy required. Topics covered at length examine advanced frameworks, path-planning, fault tolerance, machine learning, and cooperation as relevant to marine robots that need intelligent autonomy.
