Cognitive Models and Architectures

A demanding challenge in cross-cultural design is how to make a usable technology meaningful to local users. This book examines the disconnect of action and meaning in cross-cultural design and presents an innovative framework “Culturally Localized User Experience (CLUE)” to tackle the problem. Drawing from three strands of practice theories—activity theory, British cultural studies, and rhetorical genre theory, the CLUE approach regards local culture as the dynamic nexus of contextual interactions and integrates action and meaning through a dialogical, cyclical design process in order to design a technology that would engage local users within meaningful social practices. With five in-depth case studies of mobile text messaging use in American and Chinese contexts, this book demonstrates that a technology creating for a culturally localized user experience mediates both instrumental practices and social meanings. It calls for a change in cross-cultural design practices from simply applying cultural conventions in design to localizing for social affordances with rich understandings of use activities in context. Meanwhile, the vivid user stories at sites of technology-in-use show the power of “user localization” in connecting design and use, which the book believes essential for the success of an emerging technology like mobile messaging in an era of participatory culture. This book is divided into three parts: theoretical grounding for key concepts, case histories, and scholarly implications. It explores how to create culture-sensitive technology for local users in this increasingly globalized world with a rising participatory culture.

As the world deals with increasing complexity—in issues of sustainability, finance, culture, and technology—business and governments are searching for a form of problem solving that can deal with the unprecedented levels of ambiguity and chaos. Traditional "linear thinking" has been disparaged by the popular media as being inadequate for dealing with the global economic crisis. Standard forms of marketing and product development have been rejected by businesses who need to find a way to stay competitive in a global economy. Yet little has been offered as an alternative. It is not enough to demand that someone "be more innovative" without giving him the tools to succeed. Design synthesis is a way of thinking about complicated, multifaceted problems of this scale with a repeatable degree of success. Design synthesis methods can be applied in business, with the goal of producing new and compelling products and services, and they can be applied in government, with the goal of changing culture and bettering society. In both contexts, however, there is a need for speed and for aggressive action. This text is immediately relevant, and is more relevant than ever, as we acknowledge and continually reference a feeling of an impending and massive change. Simply, this text is intended to act as a practitioner's guide to exposing the magic of design.

This book takes its title from the last lecture by Allen Newell, one of the pioneers of cognitive science. He said, “The question for me is how can the human mind occur in the physical universe? We now know that the world is governed by physics. We now understand the way biology nestles comfortably within that. The issue is how will the mind do that as well?” Newell argued that the answer to his question must take the form of a cognitive architecture, and this book describes an answer that is emerging from the study of brain and behavior. Humans share the same basic cognitive architecture with all primates, but they have evolved abilities to exercise abstract control over cognition and process more complex relational patterns. The human cognitive architecture consists of a set of largely independent modules associated with different brain regions. The book discusses in detail how these various modules can combine to produce behaviors as varied as driving a car and solving an algebraic equation, but focuses principally on two of the modules: declarative and procedural. The declarative module involves a memory system that, moment by moment, attempts to give each person the most appropriate possible window into his or her past. The procedural module involves a central system that strives to develop a set of productions that will enable the most adaptive response from any state of the modules.

The field of cognitive modeling has progressed beyond modeling cognition in the context of simple laboratory tasks and begun to attack the problem of modeling cognition in more complex, realistic environments, such as those studied by researchers in the field of human factors. The problems that the human-factors community is tackling focus on modeling certain problems of communication and control that arise in the integration of implicit and explicit knowledge, emotion, and cognition, and the cognitive system with the external environment. These problems must be addressed in order to produce integrated cognitive models of moderately complex tasks. Architectures of cognition in these tasks focus on the control of a central system, which includes control of the central processor itself, initiation of functional processes, such as visual search and memory retrieval, and harvesting the results of functional processes. Because the control of the central system is conceptually different from the internal control required by individual functional processes, a complete architecture of cognition must incorporate two types of theories of control: type 1 theories of the structure, functionality, and operation of the controller, and type 2 theories of the internal control of functional processes, how, and what they communicate to the controller. This volume presents, for both types of theories, the current state of the art, as well as contrasts among current approaches to human-performance models.

Languages differ from one another in bewildering and seemingly arbitrary ways. For example, in English, the verb precedes the direct object (understand the proof), but in Japanese, the direct object comes first. In some languages, such as Mohawk, it is not even possible to establish a basic word order. Nonetheless, languages do share certain regularities in how they are structured and used. The exact nature and extent of these “language universals” has been the focus of much research and is one of the central explanatory goals in the language sciences. During the past fifty years, there has been tremendous progress, a few major conceptual revolutions, and even the emergence of entirely new fields. The wealth of findings and theories offered by the various language-science disciplines has made it more important than ever to work toward an integrated understanding of the nature of human language universals. This book examines language universals from a cross-disciplinary perspective. It provides insights into long standing questions such as: What exactly defines the human capacity for language? Are there universal properties of human languages and, if so, what are they? Can all language universals be explained in the same way, or do some universals require different kinds of explanations from others?

This book takes on one of the big questions at the heart of the cognitive sciences — what knowledge do we possess at birth, and what do we learn along the way? It is now widely accepted that evolution, individual development, and individual learning can no longer be studied in isolation from each other — they are inextricably linked. Therefore any successful theory must integrate these elements, and somehow relate them to human culture. Clearly we learn from the world around us, but that learning is skewed towards specific things about the world. We do not just attend to and learn about every stimuli that confronts us. If we did, learning would be impossibly time-consuming and ineffective. Learning is constrained — we are primed to learn about certain aspects of the world and ignore others. So what are these constraints, and where do they come from? The theory expounded in this book is that we enter the world with small amounts of innate representational knowledge. It neither sides with those who believe in ‘blank slate’ theories, nor with those who believe all learning is innate. In fact, what is written on our ‘slates’ at birth is a certain type of knowledge about specific things in the world, the general configuration of the human face for instance, a knowledge that other people possess minds and motives.

In the past twenty years, neuroimaging has provided us with a wealth of data regarding human memory. This book asks: to what extent can neuroimaging constrain, support or falsify psychological theories of memory? To what degree is research on the biological bases of memory actually guided by psychological theory? In looking at the close interaction between neuroimaging research and psychological theories of human memory, this book presents an exploration of imaging research on human memory, along with accounts of the significance of these findings with regard to fundamental psychological questions. The book starts with a summary of some of the conceptual problems we face in understanding neuroimaging data. It then looks at the four areas of human memory research that have been most intensively studied with modern brain imaging tools — learning and consolidation, working memory control processes and storage, long-term memory representations, and retrieval control processes. Throughout, the book shows how brain imaging methods, such as functional magnetic resonance imaging (fMRI) and electroencephalography (EEG), can help us increase our knowledge of how human memory is organized, how memory representations are stored, consolidated and retrieved, and how access to memory contents is controlled.

Although computational models of cognition have become very popular, these models are relatively limited in their coverage of cognition—they usually only emphasize problem solving and reasoning, or treat perception and motivation as isolated modules. The first architecture to cover cognition more broadly is the Psi theory, developed by Dietrich Dörner. By integrating motivation and emotion with perception and reasoning, and including grounded neuro-symbolic representations, the Psi contributes significantly to an integrated understanding of the mind. It provides a conceptual framework that highlights the relationships between perception and memory, language and mental representation, reasoning and motivation, emotion and cognition, autonomy and social behavior. So far, the Psi theory's origin in psychology, its methodology, and its lack of documentation have limited its impact. This book adapts the Psi theory to cognitive science and artificial intelligence, by elucidating both its theoretical and technical frameworks, and clarifying its contribution to how we have come to understand cognition.

This book attempts to resolve the Great Rationality Debate in cognitive science—the debate about how much irrationality to ascribe to human cognition. It shows how the insights of dual-process theory and evolutionary psychology can be combined to explain why humans are sometimes irrational even though they possess remarkably adaptive cognitive machinery. The book argues that to characterize fully differences in rational thinking, we need to replace dual-process theories with tripartite models of cognition. Using a unique individual differences approach, it shows that the traditional second system (System 2) of dual-process theory must be further divided into the reflective mind and the algorithmic mind. Distinguishing them gives a better appreciation of the significant differences in their key functions: the key function of the reflective mind is to detect the need to interrupt autonomous processing and to begin simulation activities, whereas that of the algorithmic mind is to sustain the processing of decoupled secondary representations in cognitive simulation. The book then uses this algorithmic/reflective distinction to develop a taxonomy of cognitive errors made on tasks in the heuristics and biases literature. It presents the empirical data to show that the tendency to make these thinking errors is not highly related to intelligence. Using a tripartite model of cognition, the book shows how, when both are properly defined, rationality is a more encompassing construct than intelligence, and that IQ tests fail to assess individual differences in rational thought. It then goes on to discuss the types of thinking processes that would be measured if rational thinking were to be assessed as IQ has been.