The San or Bushmen of southern Africa have exerted a fascination over generations of writers and scholars, from novelists and anarchists to ethnologists and geneticists, and also occupy a special place in the popular imagination as the First People and the contemporary remnant of spiritual and natural man. The ways in which particular groups of people from southern Africa have been traditionally categorised and positioned as objects of scrutiny by a range of academic disciplines is increasingly being contested and questioned. There is a growing awareness of the cultural, economic and genetic entanglement of the peoples of the region. This book examines how San and Khoe people are represented, by others, as well as by those who identify as San or Khoe. The book interrogates the ways in which disciplines, through their methodologies and ways of authorising knowledge, not only "discover" or "reveal" knowledge but produce it in ways that involve complex and often ambiguous relationships with power structures and forms of intellectual, symbolic and cultural capital. One major trend that emerges is that the San and Khoe can no longer be seen as people of the past but have to be acknowledged as contemporary and socially situated individuals and communities who are increasingly contesting the representations which others have imposed on them. This book was originally published as a special issue of Critical Arts: A Journal of South-North Cultural and Media Studies.

The representation theory of the symmetric groups is a classical topic that, since the pioneering work of Frobenius, Schur and Young, has grown into a huge body of theory, with many important connections to other areas of mathematics and physics. This self-contained book provides a detailed introduction to the subject, covering classical topics such as the Littlewood–Richardson rule and the Schur–Weyl duality. Importantly the authors also present many recent advances in the area, including Lassalle's character formulas, the theory of partition algebras, and an exhaustive exposition of the approach developed by A. M. Vershik and A. Okounkov. A wealth of examples and exercises makes this an ideal textbook for graduate students. It will also serve as a useful reference for more experienced researchers across a range of areas, including algebra, computer science, statistical mechanics and theoretical physics.

People live in cities and experience them firsthand, while urban designers explain cities conceptually. In Representation of Places Peter Bosselmann takes on the challenging question of how designers can communicate the changes they envision in order that "the rest of us" adequately understand how those changes will affect our lives. New modes of imaging technology—from two-dimensional maps, charts, and diagrams to computer models—allow professionals to explain their designs more clearly than ever before. Although architects and planners know how to read these representations, few outside the profession can interpret them, let alone understand what it would be like to walk along the streets such representations describe. Yet decisions on what gets built are significantly influenced by these very representations. A portion of Bosselmann's book is based on innovative experiments conducted at the University of California, Berkeley's Visual Simulation Laboratory. In a section titled "The City in the Laboratory," he discusses how visual simulation was applied to projects in New York City, San Francisco, and Toronto. The concerns that Bosselmann addresses have an impact on large segments of society, and lay readers as well as professionals will find much that is useful in his timely, accessibly written book.

In cognitive science, mental representations of spatial knowledge are metaphorically referred to as cognitive maps. However, investigations in cognitive psychology reveal that the cognitive map metaphor is inadequate and that more suitable conceptions of human spatial knowledge processing are needed. This book addresses mental processing of knowledge about geographic space from an AI point of view by presenting an experimental computational modeling approach. Results about human memory and visual mental imagery from cognitive psychology are combined with AI techniques of spatial and diagrammatic knowledge processing. The author develops the diagrammatic reasoning architecture MIRAGE as a comprehensive conception of human geographic knowledge processing.

Six leading experts lecture on a wide spectrum of recent results on the subject of the title. They present a survey of various interactions between representation theory and harmonic analysis on semisimple groups and symmetric spaces, and recall the concept of amenability. They further illustrate how representation theory is related to quantum computing; and much more. Taken together, this volume provides both a solid reference and deep insights on current research activity.

Knowledge about distances---along with knowledge about spatial direction---is one of the most important fundamentals for a cognitive agent's orientation, navigation, and route planning. However, only some distances can be perceived directly. Therefore, knowledge about distances must often be inferred from other sources of information. In cognitive science research on spatial cognition, this is investigated in different ways, using empirical studies, computer simulations, and knowledge representation approaches. This book presents a comprehensive interdisciplinary study of human distance cognition. It discusses results on knowledge about distances from artificial intelligence research and cognitive psychology, proposing an integrating formal framework. Focusing on knowledge about route distances, it then presents a computational model of the way in which humans infer knowledge about distances in environmental spaces like cities or buildings.

Knowledge representation is at the very core of a radical idea for understanding intelligence. Instead of trying to understand or build brains from the bottom up, its goal is to understand and build intelligent behavior from the top down, putting the focus on what an agent needs to know in order to behave intelligently, how this knowledge can be represented symbolically, and how automated reasoning procedures can make this knowledge available as needed. This landmark text takes the central concepts of knowledge representation developed over the last 50 years and illustrates them in a lucid and compelling way. Each of the various styles of representation is presented in a simple and intuitive form, and the basics of reasoning with that representation are explained in detail. This approach gives readers a solid foundation for understanding the more advanced work found in the research literature. The presentation is clear enough to be accessible to a broad audience, including researchers and practitioners in database management, information retrieval, and object-oriented systems as well as artificial intelligence. This book provides the foundation in knowledge representation and reasoning that every AI practitioner needs. - Authors are well-recognized experts in the field who have applied the techniques to real-world problems - Presents the core ideas of KR&R in a simple straight forward approach, independent of the quirks of research systems - Offers the first true synthesis of the field in over a decade