Presenting research on the computational abilities of connectionist, neural, and neurally inspired systems, this series emphasizes the question of how connectionist or neural network models can be made to perform rapid, short-term types of computation that are useful in higher level cognitive processes. The most recent volumes are directed mainly at researchers in connectionism, analogy, metaphor, and case-based reasoning, but are also suitable for graduate courses in those areas.
In the last few years, there has been an enormous amount of activity in the study of analogy and metaphor. This is partly because of an interest of artificial intelligence researchers in simulating learning processes using analogy. It also arises from critical examinations of standard theories in the philosophy of language, with their inbuilt literal/meta phoric distinction. This volume consists of recent previously unpub lished work in this area, with a particular emphasis upon the role of analogies in reasoning and, more generally, their role in thought and language. The papers are contributed by philosophers, computer scientists, cognitive scientists and literary critics. Researchers in these fields whose focus is the study of analogy and metaphor will find much of interest in this volume. These essays can also serve as an introduction to some of the major approaches taken in the investigation of analogy. As noted, this volume brings together the work of researchers in several different disciplines. The various approaches taken with respect to the understanding of analogy tend to be rather different, however, the articles suggest a common conclusion. Analogy and metaphor pervade thought and language; their close investigation thus constitutes a valuable contribution to our understanding of persons. DAVID H. HELMAN Case Western Reserve University vii PART I CONCEPTUAL AND CATEGORICAL THEORIES OF ANALOGICAL UNDERSTANDING MARK TURNER CATEGORIES AND ANALOGIES I want to pursue the following claims: The way we categorize helps explain the way we recognize a statement as an analogy.
Analogical thinking lies at the core of human cognition, pervading from the most mundane to the most extraordinary forms of creativity. By connecting poorly understood phenomena to learned situations whose structure is well articulated, it allows reasoners to expand the boundaries of their knowledge. The first part of the book begins by fleshing out the debate around whether our cognitive system is well-suited for creative analogizing, and ends by reviewing a series of studies that were designed to decide between the experimental and the naturalistic accounts. The studies confirm the psychological reality of the surface bias revealed by most experimental studies, thus claiming for realistic solutions to the problem of inert knowledge. The second part of the book delves into cognitive interventions, while maintaining an emphasis on the interplay between psychological modeling and instructional applications. It begins by reviewing the first generation of instructional interventions aimed at improving the later retrievability of educational contents by highlighting their abstract structure. Subsequent chapters discuss the most realistic avenues for devising easily-executable and widely-applicable ways of enhancing access to stored knowledge that would otherwise remain inert. The authors review results from studies from both others and their own lab that speak of the promise of these approaches.
Presenting research on the computational abilities of connectionist, neural, and neurally inspired systems, this series emphasizes the question of how connectionist or neural network models can be made to perform rapid, short-term types of computation that are useful in higher level cognitive processes. The most recent volumes are directed mainly at researchers in connectionism, analogy, metaphor, and case-based reasoning, but are also suitable for graduate courses in those areas.
Analogy has been the focus of extensive research in cognitive science over the past two decades. Through analogy, novel situations and problems can be understood in terms of familiar ones. Indeed, a case can be made for analogical processing as the very core of cognition. This is the first book to span the full range of disciplines concerned with analogy. Its contributors represent cognitive, developmental, and comparative psychology; neuroscience; artificial intelligence; linguistics; and philosophy. The book is divided into three parts. The first part describes computational models of analogy as well as their relation to computational models of other cognitive processes. The second part addresses the role of analogy in a wide range of cognitive tasks, such as forming complex cognitive structures, conveying emotion, making decisions, and solving problems. The third part looks at the development of analogy in children and the possible use of analogy in nonhuman primates. Contributors Miriam Bassok, Consuelo B. Boronat, Brian Bowdle, Fintan Costello, Kevin Dunbar, Gilles Fauconnier, Kenneth D. Forbus, Dedre Gentner, Usha Goswami, Brett Gray, Graeme S. Halford, Douglas Hofstadter, Keith J. Holyoak, John E. Hummel, Mark T. Keane, Boicho N. Kokinov, Arthur B. Markman, C. Page Moreau, David L. Oden, Alexander A. Petrov, Steven Phillips, David Premack, Cameron Shelley, Paul Thagard, Roger K.R. Thompson, William H. Wilson, Phillip Wolff
The great adventure of modern cognitive science, the discovery of the human mind, will fundamentally revise our concept of what it means to be human. Drawing together the classical conception of the language arts, the Renaissance sense of scientific discovery, and the modern study of the mind, Mark Turner offers a vision of the central role that language and the arts of language can play in that adventure.
Perception and analogy explores ways of seeing scientifically in the eighteenth century. The book examines how sensory experience is conceptualised during the period, drawing novel connections between treatments of perception as an embodied phenomenon and the creative methods employed by natural philosophers. Covering a wealth of literary, theological, and pedagogical texts that engage with astronomy, optics, ophthalmology, and the body, it argues for the significance of analogies for conceptualising and explaining new scientific ideas. As well as identifying their use in religious and topographical poetry, the book addresses how analogies are visible in material culture through objects such as orreries, camera obscuras, and aeolian harps. It makes the vital claim that scientific concepts become intertwined with Christian discourse through reinterpretations of origins and signs, the scope of the created universe, and the limits of embodied knowledge.
Perspective taking is a critical component of approaches to literature and narrative, but there is no coherent, broadly applicable, and process-based account of what it is and how it occurs. This book provides a multidisciplinary coverage of the topic, weaving together key insights from different disciplines into a comprehensive theory of perspective taking in literature and in life. The essential insight is that taking a perspective requires constructing an analogy between one's own personal knowledge and experience and that of the perspective taking target. This analysis is used to reassess a broad swath of research in mind reading and literary studies. It develops the dynamics of how analogy is used in perspective taking and the challenges that must be overcome under some circumstances. New empirical evidence is provided in support of the theory, and numerous examples from popular and literary fiction are used to illustrate the concepts. This title is part of the Flip it Open programme and may also be available Open Access. Check our website Cambridge Core for details.
This study uses conceptual metaphor theory and methodology to analyze the cultural logic and symbolic context, moral content and ethical implications of 1 Peter. Conceptual metaphor study helps explain how people generate ethical understandings; it can help us recognize and account for lively moral discourse between the NT and contemporary readers.
This volume addresses context from three comprehensive perspectives: first, its importance, the issues surrounding context, and its value in the laboratory and the field; second, the theory guiding the AI used to model its context; and third, its applications in the field (e.g., decision-making). This breadth poses a challenge. The book analyzes how the environment (context) influences human perception, cognition and action. While current books approach context narrowly, the major contribution of this book is to provide an in-depth review over a broad range of topics for a computational context no matter its breadth. The volume outlines numerous strategies and techniques from world-class scientists who have adapted their research to solve different problems with AI, in difficult environments and complex domains to address the many computational challenges posed by context. Context can be clear, uncertain or an illusion. Clear contexts: A father praising his child; a trip to the post office to buy stamps; a policewoman asking for identification. Uncertain contexts: A sneak attack; a surprise witness in a courtroom; a shout of "Fire! Fire!" Contexts as illusion: Humans fall prey to illusions that machines do not (Adelson’s checkerboard illusion versus a photometer). Determining context is not easy when disagreement exists, interpretations vary, or uncertainty reigns. Physicists like Einstein (relativity), Bekenstein (holographs) and Rovelli (universe) have written that reality is not what we commonly believe. Even outside of awareness, individuals act differently whether alone or in teams. Can computational context with AI adapt to clear and uncertain contexts, to change over time, and to individuals, machines or robots as well as to teams? If a program automatically "knows" the context that improves performance or decisions, does it matter whether context is clear, uncertain or illusory? Written and edited by world class leaders from across the field of autonomous systems research, this volume carefully considers the computational systems being constructed to determine context for individual agents or teams, the challenges they face, and the advances they expect for the science of context.
