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Artificial Intelligence is the study of how to build or program computers to enable them to do what minds can do. This volume discusses the ways in which computational ideas and computer modeling can aid our understanding of human and animal minds. Major theoretical approaches are outlined, as well as some promising recent developments. Fundamental philosophical questions are discussed along with topics such as: the differences between symbolic and connectionist AI, planning and problem solving, knowledge representation, learning, expert systems, vision, natural language, creativity, and human-computer interaction. This volume is suitable for any psychologist, philosopher, or computer scientist wanting to know the current state of the art in this area of cognitive science. Key Features * Up-to-date account of how computational ideas and techniques are relevant to psychology * Includes discussions of "classical" (symbolic) AI, of connectionism (neural nets), of evolutionary programming, and of A-Life * Discusses a wide range of psychology from low-level vision to creativity.
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The Self-Organizing Map, or Kohonen Map, is one of the most widely used neural network algorithms, with thousands of applications covered in the literature. It was one of the strong underlying factors in the popularity of neural networks starting in the early 80's. Currently this method has been included in a large number of commercial and public domain software packages. In this book, top experts on the SOM method take a look at the state of the art and the future of this computing paradigm. The 30 chapters of this book cover the current status of SOM theory, such as connections of SOM to clustering, classification, probabilistic models, and energy functions. Many applications of the SOM are given, with data mining and exploratory data analysis the central topic, applied to large databases of financial data, medical data, free-form text documents, digital images, speech, and process measurements. Biological models related to the SOM are also discussed.
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Most designers know that yellow text presented against a blue background reads clearly and easily, but how many can explain why, and what really are the best ways to help others and ourselves clearly see key patterns in a bunch of data? This book explores the art and science of why we see objects the way we do. Based on the science of perception and vision, the author presents the key principles at work for a wide range of applications--resulting in visualization of improved clarity, utility, and persuasiveness. The book offers practical guidelines that can be applied by anyone: interaction designers, graphic designers of all kinds (including web designers), data miners, and financial analysts. *First work to use the science of perception to help serious designers and analysts optimize understanding and perception of their data visualizations. * Major revision of this classic work, with a new chapter on visual thinking, new sections on face perception and flow visualization, and a much expanded chapter on color and color sequences. *New to this edition is the full color treatment throughout, to better display over 400 illustrations.
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This book is written for the students and practitioners who are looking for a single introductory Excel-based resource that covers three essential business and analytical skills—Data Analysis, Business Modeling, and Simulation of Complex Problems. The focus of the book is clearly on analysis of problems for decision making, yet detailed explanations regarding how to use Excel tools are provided. After many years of teaching and consulting, it is abundantly clear to me that for most students, a good example is worth its weight in gold. This book contains many excellent examples in each chapter, some simple and others more complex, and there is an abundance of exhibits to guide the student through the maze of steps necessary for each analysis. The content is quite diverse: • data presentation — the Feng Shui of spreadsheets, effective communication and collaboration • data preparation — import, scrub, manipulate data • data analysis — statistical methods: descriptive, inferential, and predictive, Design of Experiments • modeling — deterministic, probabilistic, What-if, Scenarios • simulation — quantifying uncertainty, Monte Carlo Simulation • optimization — constrained, Linear Programming, non-linear models, Goal Seek • Couple these features with detailed discussions of how to realistically organize and extract insight from complex problems, and I believe you have a unique educational combination in one book.
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Information Visualization: Perception for Design is a comprehensive guide to what the science of human perception tells us about how we should display information. The human brain is a super-computer for finding patterns in information. Our understanding of visual data and visual information is greatly enhanced or impeded by the way information is presented. It is essential that visual data be designed in such a way that key information and important patterns will stand out. It is only by understanding how perception works that the best visualizations can be created. Colin Ware outlines the key principles for a wide range of applications and designs, providing designers with the tools to create visualizations of improved clarity, utility and persuasiveness. The book continues to be the key resource for practical design guidelines, based on perception, which can be applied by practitioners, students and researchers alike. Complete update of the recognized source in industry, research, and academic for applicable guidance on information visualizing. Includes the latest research and state of the art information on multimedia presentation. More than 160 explicit design guidelines based on vision science. A new final chapter that explains the process of visual thinking and how visualizations help us to think about problems. Packed with over 400 informative full color illustrations, which are key to understanding of the subject. "This is a book about what the science of perception can tell us about visualization. There is a gold mine of information about how we see to be found in more than a century of work by vision researchers. The purpose of this book is to extract from that large body of research literature those design principles that apply to displaying information effectively"--
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Automated planning technology plays a significant role in a variety of demanding applications, ranging from controlling space vehicles and robots to playing the game of bridge. This book covers both the theory and practice of automated planning. It is useful for researchers, professionals, and graduate students.
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Human-Computer Interaction: An Empirical Research Perspective is the definitive guide to empirical research in HCI. The book begins with foundational topics including an historical context, the human factor, interaction elements, and the fundamentals of science and research. From there, you'll progress to learning about the methods for conducting an experiment to evaluate a new computer interface or interaction technique. There are detailed discussions and how-to analyses on models of interaction, focusing on descriptive models and predictive models. Writing and publishing a research.
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