The award-winning author of The Music of the Primes explores the future of creativity and how machine learning will disrupt, enrich, and transform our understanding of what it means to be human. Can a well-programmed machine do anything a human can-only better? Complex algorithms are choosing our music, picking our partners, and driving our investments. They can navigate more data than a doctor or lawyer and act with greater precision. For many years we've taken solace in the notion that they can't create. But now that algorithms can learn and adapt, does the future of creativity belong to machines, too? It is hard to imagine a better guide to the bewildering world of artificial intelligence than Marcus du Sautoy, a celebrated Oxford mathematician whose work on symmetry in the ninth dimension has taken him to the vertiginous edge of mathematical understanding. In The Creativity Code he considers what machine learning means for the future of creativity. The Pollockizer can produce drip paintings in the style of Jackson Pollock, Botnik spins off fanciful (if improbable) scenes inspired by J. K. Rowling, and the music-composing algorithm Emmy managed to fool a panel of Bach experts. But do these programs just mimic, or do they have what it takes to create? Du Sautoy argues that to answer this question, we need to understand how the algorithms that drive them work-and this brings him back to his own subject of mathematics, with its puzzles, constraints, and enticing possibilities. While most recent books on AI focus on the future of work, The Creativity Code moves us to the forefront of creative new technologies and offers a more positive and unexpected vision of our future cohabitation with machines. It challenges us to reconsider what it means to be human-and to crack the creativity code.

This book gathers together a set of chapters covering recent development in optimization methods that are inspired by nature. The first group of chapters describes in detail different meta-heuristic algorithms, and shows their applicability using some test or real-world problems. The second part of the book is especially focused on advanced applications and case studies. They span different engineering fields, including mechanical, electrical and civil engineering, and earth/environmental science, and covers topics such as robotics, water management, process optimization, among others. The book covers both basic concepts and advanced issues, offering a timely introduction to nature-inspired optimization method for newcomers and students, and a source of inspiration as well as important practical insights to engineers and researchers.

'A terrific book - essential reading for everyone seeking to make sense of Artificial Intelligence.' Professor Sir Adrian Smith, Director and Chief Executive of the Alan Turing Institute 'Calm, informative and refreshingly free of hype, Wooldridge's effortlessly readable book is the perfect guide to the history and future of AI.' - Tom Chivers, author of The AI Does Not Hate You In this myth-busting guide to AI past and present, one of the world's leading researchers shows why our fears for the future are misplaced. The ultimate dream of AI is to build machines that are like us: conscious and self-aware. While this remains a remote possibility, its rapid progress is already profoundly changing our world. Yet the public debate and media hype is still largely centred on unlikely prospects from sentient machines to dystopian robot takeovers. In this lively and clear-headed guide, Michael Wooldridge challenges the prevailing narrative, revealing how these anxieties distract us from both the more immediate risks that this transformative technology poses - from algorithmic bias to fake news- and the true life-changing potential of the field. The Road to Conscious Machines elucidates the discoveries of its greatest pioneers from Alan Turing to Demis Hassabis, and shows us what today's AI researchers actually think and do. AI appeals to fundamental questions about what it means to be human; so too do the failures and limitations of its past. 'Nobody understands the past, the present, the promise and the peril of this new technology better than Michael Wooldridge. The definitive account of the new AI' Matt Ridley, author of The Rational Optimist

Agents act on the basis of their beliefs and these beliefs change as they interact with other agents. In this book the authors propose and explain general logical tools for handling change. These tools include preferential reasoning, theory revision, and reasoning in inheritance systems, and the authors use these tools to examine nonmonotonic logic, deontic logic, counterfactuals, modal logic, intuitionistic logic, and temporal logic.

This book will be of benefit to researchers engaged with artificial intelligence, and in particular agents, multiagent systems and nonmonotonic logic.

The author first introduces the basic framework for cultural algorithms and he then explains the social structure of a cultural system as a mechanism for the distribution of problem-solving information throughout a population. Three different models for social organizations are presented: the homogeneous (nuclear family), heterogeneous (expanded family), and subculture (descent groups) social models. The chapters that follow compare the learning capabilities of these social organizations relative to problems of varying complexity. The book concludes with a discussion of how the results can impact our understanding of social evolution.

How can we solve engineering problems while taking into account data characterized by different types of measurement and estimation uncertainty: interval, probabilistic, fuzzy, etc.? This book provides a theoretical basis for arriving at such solutions, as well as case studies demonstrating how these theoretical ideas can be translated into practical applications in the geosciences, pavement engineering, etc. In all these developments, the authors' objectives were to provide accurate estimates of the resulting uncertainty; to offer solutions that require reasonably short computation times; to offer content that is accessible for engineers; and to be sufficiently general - so that readers can use the book for many different problems. The authors also describe how to make decisions under different types of uncertainty. The book offers a valuable resource for all practical engineers interested in better ways of gauging uncertainty, for students eager to learn and apply the new techniques, and for researchers interested in processing heterogeneous uncertainty.

'A thought-provoking look at the technology that is changing the world of business and the benefits, pitfalls, and challenges for society as a whole.' - Kenneth I. Chenault, former chief executive officer, American Express Company Throughout the twentieth century, technology and economics drove a dominant logic: bigger was almost always better. It was smart to scale up - to take advantage of classic economies of scale. But in the unscaled economy, size and scale have become a liability. Today's most successful companies - Uber, Airbnb, Amazon, Salesforce - have defied the traditional 'economies of scale' approach by renting scale instead of spending vast amounts of money building it. And a new generation of upstarts is using artificial intelligence to automate tasks that once required expensive investment, enabling them to grow big without the bloat of giant organisations. In Unscaled, Hemant Taneja convincingly shows how the unscaled economy is remaking massive, deeply-rooted industries and opening up fantastic possibilities for entrepreneurs, imaginative companies and resourceful individuals. Beyond that, it can be the model for solving some of the world's greatest problems, including climate change and soaring healthcare costs, potentially reversing many of the ills brought on by mass industrialization. The unscale wave has only just started. To succeed in business today, companies, CEOs and leaders everywhere must unlearn what they have been taught - they must embrace an unscaled mindset.

This book offers readers an essential introduction to the fundamentals of digital image processing. Pursuing a signal processing and algorithmic approach, it makes the fundamentals of digital image processing accessible and easy to learn. It is written in a clear and concise manner with a large number of 4 x 4 and 8 x 8 examples, figures and detailed explanations. Each concept is developed from the basic principles and described in detail with equal emphasis on theory and practice. The book is accompanied by a companion website that provides several MATLAB programs for the implementation of image processing algorithms. The book also offers comprehensive coverage of the following topics: Enhancement, Transform processing, Restoration, Registration, Reconstruction from projections, Morphological image processing, Edge detection, Object representation and classification, Compression, and Color processing.

This book focuses on approximations under the presence of ordinary and fractional smoothness, presenting both the univariate and multivariate cases. It also explores approximations under convexity and a new trend in approximation theory -approximation by sublinear operators with applications to max-product operators, which are nonlinear and rational providing very fast and flexible approximations. The results presented have applications in numerous areas of pure and applied mathematics, especially in approximation theory and numerical analysis in both ordinary and fractional senses. As such this book is suitable for researchers, graduate students, and seminars of the above disciplines, and is a must for all science and engineering libraries.

This book constitutes the refereed proceedings of the 13th IFIP WG 5.1 International Conference on Product Lifecycle Management, PLM 2016, held in Columbia, SC, USA, in July 2016. The 57 revised full papers presented were carefully reviewed and selected from 77 submissions. The papers are organized in the following topical sections: knowledge sharing, re-use and preservation; collaborative development architectures; interoperability and systems integration; lean product development and the role of PLM; PLM and innovation; PLM tools; cloud computing and PLM tools; traceability and performance; building information modeling; big data analytics and business intelligence; information lifecycle management; industry 4.0; metrics, standards and regulation; and product, service and systems.

This book introduces and illustrates modeling, sensing, and control methods for analyzing, designing, and developing spherical motors. It systematically presents models for establishing the relationships among the magnetic fields, position/orientation and force/torque, while also providing time-efficient solutions to assist researchers and engineers in studying and developing these motors. In order to take full advantage of spherical motors' compact structure in practical applications, sensing and control methods that utilize their magnetic fields and eliminate the need to install external sensors for feedback are proposed. Further, the book investigates for the first time spherical motors' force/torque manipulation capability, and proposes algorithms enabling the ball-joint-like end-effector for haptic use based on these motors' hybrid position/force actuation modes. While systematically presenting approaches to their design, sensing and control, the book also provides many examples illustrating the implementation issues readers may encounter.

This journal subline serves as a forum for stimulating and disseminating innovative research ideas, theories, emerging technologies, empirical investigations, state-of-the-art methods, and tools in all different genres of edutainment, such as game-based learning and serious games, interactive storytelling, virtual learning environments, VR-based education, and related fields. It covers aspects from educational and game theories, human-computer interaction, computer graphics, artificial intelligence, and systems design. The 19 papers presented in the 14th issue were organized in topical sections named: 3D modeling and visualization; image; e-learning and games; and miscellaneous.

By presenting the latest advances in fuzzy sets and computing with words from around the globe, this book disseminates recent innovations in advanced intelligent technologies and systems. From intelligent control and intuitionistic fuzzy quantifiers to various data science and industrial applications, it includes a wide range of valuable lessons learned and ideas for future intelligent products and systems.

This book addresses the issue of Machine Learning (ML) attacks on Integrated Circuits through Physical Unclonable Functions (PUFs). It provides the mathematical proofs of the vulnerability of various PUF families, including Arbiter, XOR Arbiter, ring-oscillator, and bistable ring PUFs, to ML attacks. To achieve this goal, it develops a generic framework for the assessment of these PUFs based on two main approaches. First, with regard to the inherent physical characteristics, it establishes fit-for-purpose mathematical representations of the PUFs mentioned above, which adequately reflect the physical behavior of these primitives. To this end, notions and formalizations that are already familiar to the ML theory world are reintroduced in order to give a better understanding of why, how, and to what extent ML attacks against PUFs can be feasible in practice. Second, the book explores polynomial time ML algorithms, which can learn the PUFs under the appropriate representation. More importantly, in contrast to previous ML approaches, the framework presented here ensures not only the accuracy of the model mimicking the behavior of the PUF, but also the delivery of such a model. Besides off-the-shelf ML algorithms, the book applies a set of algorithms hailing from the field of property testing, which can help to evaluate the security of PUFs. They serve as a "toolbox", from which PUF designers and manufacturers can choose the indicators most relevant for their requirements. Last but not least, on the basis of learning theory concepts, the book explicitly states that the PUF families cannot be considered as an ultimate solution to the problem of insecure ICs. As such, it provides essential insights into both academic research on and the design and manufacturing of PUFs.

This book contains extended version of selected works that have been discussed and presented in the fourth International Doctoral Symposium on Applied Computation and Security Systems (ACSS 2017) held in Patna, India during March 17-19, 2017. The symposium was organized by the Departments of Computer Science & Engineering and A. K. Choudhury School of Information Technology, both from University of Calcutta in collaboration with NIT, Patna. The International partners for ACSS 2016 had been Ca Foscari University of Venice, Italy and Bialystok University of Technology, Poland. This bi-volume book has a total of 21 papers divided in 7 chapters. The chapters reflect the sessions in which the works have been discussed during the symposium. The different chapters in the book include works on biometrics, image processing, pattern recognition, algorithms, cloud computing, wireless sensor networks and security systems.

This book focuses on the stabilization and model predictive control of interconnected systems with mixed connection configurations. It introduces the concept of dissipation-based quadratic constraint for developing attractivity assurance methods for interconnected systems. In order to develop these methods, distributed and decentralized architectures are employed, whereby the communication between subsystems is fully connected, partially connected, or completely disconnected. Given that the control inputs are entirely or partially decoupled between subsystems and no additional constraints are imposed on the interactive variables beyond the coupling constraint itself, the proposed approaches can be used with various types of systems and applications. Further, the book describes how the effects of coupling delays and data losses in device networks are resolved. From a practical perspective, the innovations presented are of benefit in applications in a broad range of fields, including the process and manufacturing industries, networked robotics, and network-centric systems such as chemical process systems, power systems, telecommunication networks, transportation networks, and, no less importantly, supply chain automation.

This book is a collection of selected papers from the 2011 International Conference on Communications, Electronics and Automation Engineering hold in Xi an, China, August 23-25, 2012. It presents some of the latest research findings in a broad range of interdisciplinary fields related to communications, electronics and automation engineering. Specific emphasis is placed on the following topics: automation control, data mining and statistics, simulation and mathematical modeling, human factors and cognitive engineering, web technology, optimization and algorithm, and network communications. The prime objective of the book is to familiarize the readers with cutting edge developments in the research of electronics and automation engineering with a variety of applications. Hopefully, the book can help researchers to identify research trends in many areas, to learn the new methods and tools, and to spark innovative ideas. "

This book includes recent research on Hybrid Intelligent Systems. It presents 35 selected papers from the 17th edition of the International Conference on Hybrid Intelligent Systems (HIS), which was held in Delhi, India from December 14 to 16, 2017. Reflecting the awareness in the respective academic communities that combined approaches are essential to solving the remaining tough problems in computational intelligence, the HIS is a premier conference focused on the hybridization of intelligent systems. The book offers a valuable reference guide for all researchers, students and practitioners in the fields of Computer Science and Engineering.

Learn how to implement and build a neural network with this non-technical, project-based book as your guide. As you work through the chapters, you'll build an electronics project, providing a hands-on experience in training a network. There are no prerequisites here and you won't see a single line of computer code in this book. Instead, it takes a hardware approach using very simple electronic components. You'll start off with an interesting non-technical introduction to neural networks, and then construct an electronics project. The project isn't complicated, but it illustrates how back propagation can be used to adjust connection strengths or "weights" and train a network. By the end of this book, you'll be able to take what you've learned and apply it to your own projects. If you like to tinker around with components and build circuits on a breadboard, Neural Networks for Electronics Hobbyists is the book for you. What You'll Learn Gain a practical introduction to neural networks Review techniques for training networks with electrical hardware and supervised learning Understand how parallel processing differs from standard sequential programming Who This Book Is For Anyone interest in neural networks, from electronic hobbyists looking for an interesting project to build, to a layperson with no experience. Programmers familiar with neural networks but have only implemented them using computer code will also benefit from this book.

This book presents the latest findings on the subject of combustion optimization based on computational intelligence. It covers a broad range of topics, including the modeling of coal combustion characteristics based on artificial neural networks and support vector machines. It also describes the optimization of combustion parameters using genetic algorithms or ant colony algorithms, an online coal optimization system, etc. Accordingly, the book offers a unique guide for researchers in the areas of combustion optimization, NOx emission control, energy and power engineering, and chemical engineering.

This book highlights the latest findings on nonlinear dynamical systems including two types of attractors: self-excited and hidden attractors. Further, it presents both theoretical and practical approaches to investigating nonlinear dynamical systems with self-excited and hidden attractors. The book includes 20 chapters contributed by respected experts, which focus on various applications such as biological systems, memristor-based systems, fractional-order systems, finance systems, business cycles, oscillators, coupled systems, hyperchaotic systems, flexible robot manipulators, electronic circuits, and control models. Special attention is given to modeling, design, circuit realization, and practical applications to address recent research problems in nonlinear dynamical systems. The book provides a valuable reference guide to nonlinear dynamical systems for engineers, researchers, and graduate students, especially those whose work involves mechanics, electrical engineering, and control systems.

The book offers a comprehensive, practice-oriented introduction to the field of fuzzy mathematical programming (FMP) as key topic of modern analytics. FMP plays a fundamental role in dealing with a varied range of problems, such as those concerning smart cities, sustainability, and renewable energies. This book includes an introduction to the basic concepts, together with extensive information on the computational-intelligence-based optimization models and techniques that have been used to date. Special emphasis is given to fuzzy transportation problems. The book is a valuable resource for researchers, data scientists and practitioners dealing with computational-intelligence-based optimization models for analytics.

The thesis presents new results on multi-agent formation control, focusing on the distributed stabilization control of rigid formation shapes. It analyzes a range of current research problems such as problems concerning the equilibrium and stability of formation control systems, or the problem of cooperative coordination control when agents have general dynamical models, and discusses practical considerations arising during the implementation of established formation control algorithms. In addition, the thesis presents models of increasing complexity, from single integrator models, to double integrator models, to agents modeled by nonlinear kinematic and dynamic equations, including the familiar unicycle model and nonlinear system equations with drift terms. Presenting the fruits of a close collaboration between several top control groups at leading universities including Yale University, Groningen University, Purdue University and Gwangju Institute of Science and Technology (GIST), the thesis spans various research areas, including robustness issues in formations, quantization-based coordination, exponential stability in formation systems, and cooperative coordination of networked heterogeneous systems.

This book offers an introduction to artificial adaptive systems and a general model of the relationships between the data and algorithms used to analyze them. It subsequently describes artificial neural networks as a subclass of artificial adaptive systems, and reports on the backpropagation algorithm, while also identifying an important connection between supervised and unsupervised artificial neural networks. The book's primary focus is on the auto contractive map, an unsupervised artificial neural network employing a fixed point method versus traditional energy minimization. This is a powerful tool for understanding, associating and transforming data, as demonstrated in the numerous examples presented here. A supervised version of the auto contracting map is also introduced as an outstanding method for recognizing digits and defects. In closing, the book walks the readers through the theory and examples of how the auto contracting map can be used in conjunction with another artificial neural network, the "spin-net," as a dynamic form of auto-associative memory.

Robotic Sailing 2017. This book contains the peer-reviewed papers presented at the 10th International Robotic Sailing Conference which was organized in conjunction with the 10th World Robotic Sailing Championship held in Horten, Norway the 4th-9th of September 2017. The seven papers cover topics of interest for autonomous robotic sailing which represents some of the most challenging research and development areas. The book is divided into two parts. The first part contains papers which focus on the design of sails and software for the assessment and predication of sailboat performance as well as software platforms and middleware for sailboat competition and research. The second part includes algorithms and strategies for navigation and collision avoidance on local, mid- and long range. The differences in approach in the included papers show that robotic sailing is still an emerging cross-disciplinary science. The multitude of suggestions to the specific problems of prediction and simulation of sailboats as well as the challenges of route planning, anti-grounding and collision avoidance are good indicators of science in its infancy. Hence, we may expect the future to hold great advances for robotic sailing.