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Through a comprehensive computational theory of the mind, namely, a computational “cognitive architecture”, this book explores cognitive or psychological mechanisms and processes. The goal of this book is to develop a unified framework for understanding the human mind, and within the unified framework, to develop process-based, mechanistic understanding of a variety of psychological phenomena. Specifically, the book first describes the essential CLARION framework and its cognitive-psychological justifications, then its computational instantiations, and finally its applications to capturing, simulating, and explaining various psychological phenomena and empirical data. Through the lens of a unified framework, the book shows how the models and simulations shed light on psychological mechanisms and processes. In fields ranging from cognitive science, to psychology, to artificial intelligence, and even to philosophy, academic researchers, graduate and undergraduate students, and practitioners of various kinds may have interest in topics covered by this book. The book may also be suitable for seminars or courses at graduate or undergraduate levels on cognitive architectures or cognitive modeling (i.e., computational psychology).

Minds enable people to perceive, imagine, solve problems, understand, learn, speak, reason, create, and be emotional and conscious. Competing explanations of how the mind works have identified it as soul, computer, brain, dynamical system, or social construction. This book explains minds in terms of interacting mechanisms operating at multiple levels, including the social, mental, neural, and molecular. Brain–Mind presents a unified, brain-based theory of cognition and emotion with applications to the most complex kinds of thinking, right up to consciousness and creativity. Unification comes from systematic application of Chris Eliasmith’s powerful new Semantic Pointer Architecture, a highly original synthesis of neural network and symbolic ideas about how the mind works. The book shows the relevance of semantic pointers to a full range of important kinds of mental representations, from sensations and imagery to concepts, rules, analogies, and emotions. Neural mechanisms are used to explain many phenomena concerning consciousness, action, intention, language, creativity, and the self. This book belongs to a trio that includes Mind–Society: From Brains to Social Sciences and Professions and Natural Philosophy: From Social Brains to Knowledge, Reality, Morality, and Beauty. They can be read independently, but together they make up a Treatise on Mind and Society that provides a unified and comprehensive treatment of the cognitive sciences, social sciences, professions, and humanities.

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.

How do “minds” work? In Exploring Robotic Minds: Actions, Symbols, and Consciousness as Self-Organizing Dynamic Phenomena, Professor Jun Tani reviews key experiments within his own pioneering neurorobotics research project aimed at answering this fundamental and fascinating question. The book shows how symbols and concepts representing the world can emerge via “deep learning” within robots, by using specially designed neural network architectures by which, given iterative interactions between top-down proactive “subjective” and “intentional” processes for plotting action, and bottom-up updates of the perceptual reality after action, the robot is able to learn to isolate, to identify, and even to infer salient features of the operational environment, modifying its behavior based on anticipations of both objective and social cues. Through permutations of this experimental model, the book then argues that longstanding questions about the nature of “consciousness” and “freewill” can be addressed through an understanding of the dynamic structures within which, in the course of normal operations and in a changing operational environment, necessary top-down/bottom-up interactions arise. Written in clear and accessible language, this book opens a privileged window for a broad audience onto the science of artificial intelligence and the potential for artificial consciousness, threading cognitive neuroscience, dynamic systems theory, robotics, and phenomenology through an elegant series of deceptively simple experiments that build upon one another and ultimately outline the fundamental form of the working mind.

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.

For more than 2000 years Greek philosophers have thought about the puzzling introspectively assessed dichotomy between our physical bodies and our seemingly non-physical minds. How is it that we can think highly abstract thoughts, seemingly fully detached from actual, physical reality? Despite the obvious interactions between mind and body (we get tired, we are hungry, we stay up late despite being tired, etc.), until today it remains puzzling how our mind controls our body, and vice versa, how our body shapes our mind. Despite a big movement towards embodied cognitive science over the last 20 years or so, introductory books with a functional and computational perspective on how human thought and language capabilities may actually have come about – and are coming about over and over again – are missing. This book fills that gap. Starting with a historical background on traditional cognitive science and resulting fundamental challenges that have not been resolved, embodied cognitive science is introduced and its implications for how human minds have come and continue to come into being are detailed. In particular, the book shows that evolution has produced biological bodies that provide “morphologically intelligent” structures, which foster the development of suitable behavioral and cognitive capabilities. While these capabilities can be modified and optimized given positive and negative reward as feedback, to reach abstract cognitive capabilities, evolution has furthermore produced particular anticipatory control-oriented mechanisms, which cause the development of particular types of predictive encodings, modularizations, and abstractions. Coupled with an embodied motivational system, versatile, goal-directed, self-motivated behavior, learning becomes possible. These lines of thought are introduced and detailed from interdisciplinary, evolutionary, ontogenetic, reinforcement learning, and anticipatory predictive encoding perspectives in the first part of the book. A short excursus then provides an introduction to neuroscience, including general knowledge about brain anatomy, and basic neural and brain functionality, as well as the main research methodologies. With reference to this knowledge, the subsequent chapters then focus on how the human brain manages to develop abstract thought and language. Sensory systems, motor systems, and their predictive, control-oriented interactions are detailed from a functional and computational perspective. Bayesian information processing is introduced along these lines as are generative models. Moreover, it is shown how particular modularizations can develop. When control and attention come into play, these structures develop also dependent on the available motor capabilities. Vice versa, the development of more versatile motor capabilities depends on structural development. Event-oriented abstractions enable conceptualizations and behavioral compositions, paving the path towards abstract thought and language. Also evolutionary drives towards social interactions play a crucial role. Based on the developing sensorimotor- and socially-grounded structures, the human mind becomes language ready. The development of language in each human child then further facilitates the self-motivated generation of abstract, compositional, highly flexible thought about the present, past, and future, as well as about others. In conclusion, the book gives an overview over how the human mind comes into being – sketching out a developmental pathway towards the mastery of abstract and reflective thought, while detailing the critical body and neural functionalities, and computational mechanisms, which enable this development.

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?

Social change comes from the combination of communication among people and their individual cognitive and emotional processes. This book systematically connects neural and psychological explanations of mind with social phenomena, covering major social sciences (social psychology, sociology, politics, economics, anthropology, and history) and professions (medicine, law, education, engineering, and business). The aim is not to reduce the social to the psychological but rather to display their harmony and interdependence. This display is accomplished by describing the interconnections among mental and social mechanisms, which interact to generate social changes ranging from marriage patterns to wars. The major tool for this description is the method of social cognitive-emotional workups, which connects the mental mechanisms operating in individuals with social mechanisms operating in groups. Social change is the result of emergence from interacting social and mental mechanisms, which include the neural and molecular processes that make minds capable of thinking. Validation of hypotheses about multilevel emergence requires detailed studies of important social changes, from norms about romantic relationships to economic practices, political institutions, religious customs, and international relations. This book belongs to a trio that includes Brain–Mind: From Neurons to Consciousness and Creativity and Natural Philosophy: From Social Brains to Knowledge, Reality, Morality, and Beauty. They can be read independently, but together they make up a Treatise on Mind and Society that provides a unified and comprehensive treatment of the cognitive sciences, social sciences, professions, and humanities.

The book presents theoretical, methodological, and technical advances in the study of norms in societies of autonomous intelligent agents, based on a collaboration among social, computational, and cognitive scientists. By conceptualizing norms as social and cognitive phenomena undergoing a complex dynamics, and thanks to a computational, agent-based approach, contributors address three sets of questions: (a) What are norms, and how may we differentiate them from social conformism on one hand and acquiescence under menace on the other? (b) How do norms emerge and change? An innovative answer is found in the interplay between the mental and social dynamics of norms. (c) How can we characterize the agents from among which norms emerge, why and how people represent norms and abide with or violate them in a non-necessarily deliberative way? Throughout the book, the surprise is that conformity is only the tip of the normative iceberg. Norms emerge in society while “immerging” into the mind. Their mental dynamics, occurring beneath the line of observation, allows all the sets of questions to be answered: a special agent architecture is needed for norm immergence, which in turn allows us to account for how norm-based behavior emerges as a special form of social regularity. After a review of different approaches, the volume presents a dynamic model of norms, the normative agent architecture, a simulation platform, and the artificial experiments testing the view of norms and the architecture proposed against a number of more or less realistic social scenarios.

Philosophy is the attempt to answer general questions about the nature of knowledge, reality, and values. Natural philosophy draws heavily on the sciences and finds no room for supernatural entities such as souls, gods, and possible worlds. Paul Thagard develops interconnected theories of knowledge, reality, morality, justice, meaning, and the arts. He uses new theories of brain mechanisms and social interactions to forge original accounts of the traditional branches of philosophy, including epistemology, metaphysics, ethics, and aesthetics. Rather than reducing the humanities to the sciences, this book displays fertile interconnections that show that philosophical questions and artistic practices can be much better understood by considering how human brains operate and interact in social contexts. The sciences and the humanities are interdependent, because both the natural and social sciences cannot avoid questions about methods and values that are primarily the province of philosophy. Rather than diminish philosophy, the goal of this book is to show its importance for diverse human enterprises, including science, politics, the arts, and everyday life. Natural philosophy draws on the sciences to dramatically increase understanding of fundamental issues concerning mind, meaning, and morality. This book belongs to a trio that includes Brain–Mind: From Neurons to Consciousness and Creativity and Mind–Society: From Brains to Social Sciences and Professions. They can be read independently, but together they make up a Treatise on Mind and Society that provides a unified and comprehensive treatment of the cognitive sciences, social sciences, professions, and humanities.

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.

This book elaborates a series of contributions to a non–representational theory of action and perception. It is based on current theoretical developments in the enactive approach to life and mind. These enactive ideas are applied and extended to provide a theoretically rich, naturalistic account of sensorimotor meaning and agency. This account supplies non–representational extensions to the sensorimotor approach to perceptual experience based on the notion of the living body as a self–organizing dynamic system in coupling with the environment. The enactive perspective entails the use of world–involving explanations, in which processes external to an agent co–constitute mental phenomena in ways that cannot be reduced to the supply of information for internal processing. These contributions to sensorimotor theories are a dynamical–systems description of different types of sensorimotor regularities or sensorimotor contingencies, a dynamical interpretation of Piaget's theory of equilibration to ground the concept of sensorimotor mastery, and a theory of agency as organized networks of sensorimotor schemes, with its implications for sensorimotor subjectivity. New tools are provided for examining the organization, development, and operation of networks of sensorimotor schemes that compose regional activities and genres of action with their own situated norms. This permits the exploration of new explanations for the phenomenology of agency experience that are favorably contrasted with traditional computational approaches and lead to new empirical predictions. From these proposals, capabilities once beyond the reach of enactive explanations, such as the possibility of virtual actions and the adoption of socially mediated abstract perceptual attitudes, can be addressed.

Motion profoundly shapes human social interactions. Researchers across a surprising diversity of scientific and technical fields are attempting to measure, understand and possibly harness the impact emotion’s role in shaping interactions between people and between people and technology. Concepts like rapport, emotional contagion or emergent emotions presuppose people rapidly detect nonverbal affective cues, make inferences about the other party’s mental state, and respond in ways that jointly shape the success or failure of social interactions. Recent advances in artificial intelligence are allowing computer systems to engage in this nonverbal dance, on the one hand opening a wealth of possibilities for human-machine systems, and on the other, creating powerful new tools for behavioral science research. This book reports on the state-of-the-art in both social science theory and computational methods, and illustrates how these two fields, together, can both facilitate and illuminate human social processes. The book has several aims: • Present current social science theories of social emotions from cognitive, biological, social and developmental perspectives • Strengthen the theoretical foundation for building computational systems that co-construct emotional trajectories with human participants • Discuss computational models of social cognition that can represent and reason about the evolving relationship between interaction partners • Present the current and future potential of sensing technology to reliably detect and classify affective nonverbal cues • Discuss the potential of computational methods as tools for empirical research into human transactional processes • Consider methodological approaches for assessing the social consequences of socio-emotional systems