Inventing Intelligence

This book chronicles how successive generations of natural philosophers, geologists and geomorphologists have come to invent the view of the Earth over the past 250 years. Chronicles how successive generations of natural philosophers, geologists and geomorphologists have come to invent different views of the Earth over the last 250 years. Uses as its central viewpoint changing ideas about the significance of the action of rain and rivers on the Earth’s surface. Shows how our contemporary “truths” have come to be accepted and exposes the frailty of even the most impeccably scientific visions of the Earth.

Intelligence: A Brief History is a lively and accessible look at the origins of the field of intelligence. The book explores the nature and measurement of intelligence, examines approaches to teaching intelligence, and discusses individual and group differences in intelligence. Readers will receive an historical overview of the field as well as a good understanding of its major ideas.

Computational Intelligence: An Introduction, Second Edition offers an in-depth exploration into the adaptive mechanisms that enable intelligent behaviour in complex and changing environments. The main focus of this text is centred on the computational modelling of biological and natural intelligent systems, encompassing swarm intelligence, fuzzy systems, artificial neutral networks, artificial immune systems and evolutionary computation. Engelbrecht provides readers with a wide knowledge of Computational Intelligence (CI) paradigms and algorithms; inviting readers to implement and problem solve real-world, complex problems within the CI development framework. This implementation framework will enable readers to tackle new problems without any difficulty through a single Java class as part of the CI library. Key features of this second edition include: A tutorial, hands-on based presentation of the material. State-of-the-art coverage of the most recent developments in computational intelligence with more elaborate discussions on intelligence and artificial intelligence (AI). New discussion of Darwinian evolution versus Lamarckian evolution, also including swarm robotics, hybrid systems and artificial immune systems. A section on how to perform empirical studies; topics including statistical analysis of stochastic algorithms, and an open source library of CI algorithms. Tables, illustrations, graphs, examples, assignments, Java code implementing the algorithms, and a complete CI implementation and experimental framework. Computational Intelligence: An Introduction, Second Edition is essential reading for third and fourth year undergraduate and postgraduate students studying CI. The first edition has been prescribed by a number of overseas universities and is thus a valuable teaching tool. In addition, it will also be a useful resource for researchers in Computational Intelligence and Artificial Intelligence, as well as engineers, statisticians, operational researchers, and bioinformaticians with an interest in applying AI or CI to solve problems in their domains. Check out http://www.ci.cs.up.ac.za for examples, assignments and Java code implementing the algorithms.

Computational Intelligence: Synergies of Fuzzy Logic, Neural Networks and Evolutionary Computing presents an introduction to some of the cutting edge technological paradigms under the umbrella of computational intelligence. Computational intelligence schemes are investigated with the development of a suitable framework for fuzzy logic, neural networks and evolutionary computing, neuro-fuzzy systems, evolutionary-fuzzy systems and evolutionary neural systems. Applications to linear and non-linear systems are discussed with examples. Key features: Covers all the aspects of fuzzy, neural and evolutionary approaches with worked out examples, MATLAB® exercises and applications in each chapter Presents the synergies of technologies of computational intelligence such as evolutionary fuzzy neural fuzzy and evolutionary neural systems Considers real world problems in the domain of systems modelling, control and optimization Contains a foreword written by Lotfi Zadeh Computational Intelligence: Synergies of Fuzzy Logic, Neural Networks and Evolutionary Computing is an ideal text for final year undergraduate, postgraduate and research students in electrical, control, computer, industrial and manufacturing engineering.

* Focuses on learning patterns and knowledge from data generated by mobile users and mobile technology. * Covers research and application issues in applying computational intelligence applications to mobile computing * Delivers benefits to a wide range of applications * Introduces the state of the art of computational intelligence to the mobile paradigm

A leap forward in the field of robotics Until now, most of the advances in robotics have taken place in structured environments. Scientists and engineers have designed highly sophisticated robots, but most are still only able to operate and move in predetermined, planned environments designed specifically for the robots and typically at very high cost. This new book takes robotics to the next level by setting forth the theory and techniques needed to achieve robotic motion in unstructured environments. The ability to move and operate in an arbitrary, unplanned environment will lead to automating a wide range of new robotic tasks, such as patient care, toxic site cleanup, and planetary exploration. The approach that opens the door for robots to handle unstructured tasks is known as Sensing-Intelligence-Motion (SIM), which draws from research in topology, computational complexity, control theory, and sensing hardware. Using SIM as an underlying foundation, the author's carefully structured presentation is designed to: * Formulate the challenges of sensor-based motion planning and then build a theoretical foundation for sensor-based motion planning strategies * Investigate promising algorithmic strategies for mobile robots and robot arm manipulators, in both cases addressing motion planning for the whole robot body * Compare robot performance to human performance in sensor-based motion planning to gain better insight into the challenges of SIM and help build synergistic human-robot teams for tele-operation tasks. It is both exciting and encouraging to discover that robot performance decisively exceeds human performance in certain tasks requiring spatial reasoning, even when compared to trained operators * Review sensing hardware that is necessary to realize the SIM paradigm Some 200 illustrations, graphic sketches, and photos are included to clarify key issues, develop and validate motion planning approaches, and demonstrate full systems in operation. As the first book fully devoted to robot motion planning in unstructured environments, Sensing, Intelligence, Motion is a must-read for engineers, scientists, and researchers involved in robotics. It will help them migrate robots from highly specialized applications in factories to widespread use in society where autonomous robot motion is needed.

Provides an in-depth and even treatment of the three pillars of computational intelligence and how they relate to one another This book covers the three fundamental topics that form the basis of computational intelligence: neural networks, fuzzy systems, and evolutionary computation. The text focuses on inspiration, design, theory, and practical aspects of implementing procedures to solve real-world problems. While other books in the three fields that comprise computational intelligence are written by specialists in one discipline, this book is co-written by current former Editor-in-Chief of IEEE Transactions on Neural Networks and Learning Systems, a former Editor-in-Chief of IEEE Transactions on Fuzzy Systems, and the founding Editor-in-Chief of IEEE Transactions on Evolutionary Computation. The coverage across the three topics is both uniform and consistent in style and notation. Discusses single-layer and multilayer neural networks, radial-basis function networks, and recurrent neural networks Covers fuzzy set theory, fuzzy relations, fuzzy logic interference, fuzzy clustering and classification, fuzzy measures and fuzzy integrals Examines evolutionary optimization, evolutionary learning and problem solving, and collective intelligence Includes end-of-chapter practice problems that will help readers apply methods and techniques to real-world problems Fundamentals of Computational intelligence is written for advanced undergraduates, graduate students, and practitioners in electrical and computer engineering, computer science, and other engineering disciplines.

The book contains the papers developed from the presentations at the Distributed Intelligence in Design Symposium, held in Salford in May 2009. In this context, Distributed Intelligence refers to the interdisciplinary knowledge of a range of different individuals in different organisations, with different backgrounds and experience, and the symposium discussed the media, technologies and behaviours required to support their successful collaboration. The book focusses on: how parametric and generative design media can be coupled with and managed alongside Building Information Modelling tools and systems how the cross-disciplinary knowledge is distributed and coordinated across different software, participants and organizations the characteristics of the evolving creative and collaborative practices how built environment education should be adapted to this digitally-networked practice and highly distributed intelligence in design The chapters address a range of innovative developments, methodologies, applications, research work and theoretical arguments, to present current experience and expectations as collaborative practice becomes critical in the design of future built environments.

Combining biology, computer science, mathematics, and statistics, the field of bioinformatics has become a hot new discipline with profound impacts on all aspects of biology and industrial application. Now, Computational Intelligence in Bioinformatics offers an introduction to the topic, covering the most relevant and popular CI methods, while also encouraging the implementation of these methods to readers' research.

Organizations, both private and public, are now evolving in a globalized information society that has been accelerated by digitization. They find themselves drawn into a spiral of transformations fueled by the incessant reinvention of information and communication technologies (ICT) that are changing digital uses and practices. They transform through the mediating action of ICTs, work activities and associated action situations.

Platform and Collective Intelligence analyzes a specific declination of an organization that has become irreversibly reticular: the platform organization. The network, at the heart of this new conception, proposes a model combining cybernetics and computing. The organization can thus be seen as an interface for contact, via its information systems, for employees or citizens, whatever their geographical location.

With a view going beyond technocentrism and technological determinism, this book combines collective intelligence and sociotechnics with the platform to arrive at the notion of organizational experience.