Sketching is a powerful means of working out and communicating ideas. Sketch understanding involves a combination of visual, spatial, and conceptual knowledge and reasoning, which makes it both challenging to model and potentially illuminating for cognitive science. This paper describes CogSketch, an ongoing effort of the NSF-funded Spatial Intelligence and Learning Center, which is being developed both as a research instrument for cognitive science and as a platform for sketch-based educational software. We describe the idea (...) of open-domain sketch understanding, the scientific hypotheses underlying CogSketch, and provide an overview of the models it employs, illustrated by simulation studies and ongoing experiments in creating sketch-based educational software. (shrink)

Cognitive science of religion (CSR) has increased influence in religious studies, the resistance of religious protectionists notwithstanding. CSR's most provocative work stresses the role of implicit cognition in explaining religious thought and conduct. Exhibiting explanatory pluralism, CSR seeks integrative accounts across the social, psychological, and brain sciences. CSR reflects prominent trends in the cognitive sciences generally. First, CSR is giving greater attention to the new tools and findings of cognitive neuroscience. Second, CSR researchers have done carefully (...) designed, nonlaboratory studies of experience, incorporating precise physiological measures, obtaining astonishing findings about the experiences of ritual participants and observers. Third, CSR theorists have advanced evolutionary hypotheses about religions from eight perspectives (cross-indexing three levels of selection with three mechanisms of selection). Cultural group selectionists headline credibility enhancing displays and Big Gods in the religious consolidation of large-scale societies. Other CSR researchers marshal counterevidence and advance alternative hypotheses. CSR findings are incompatible with the New Atheists’ projects on two fronts. (shrink)

Purpose: This paper is a brief introduction to enactive cognitive science: a description of some of the main research concerns; some examples of how such concerns have been realized in actual research; some of its research methods and proposed explanatory mechanisms and models; some of the potential as both a theoretical and applied science; and several of the major open research questions. Findings: Enactive cognitive science is an approach to the study (...) of mind that seeks to explain how the structures and mechanisms of autonomous cognitive systems can arise and participate in the generation and maintenance of viable perceiver-dependent worlds -- rather than more conventional cognitivist efforts, such as the attempt to explain cognition in terms of the ``recovery'' of (pre-given, timeless) features of The (objectively-existing and accessible) World. As such, enactive cognitive science is resonant with radical constructivism. Research implications: As with other scientific efforts conducted within a constructivist orientation, enactive cognitive science is broadly ``conventional'' in its scientific methodology. That is, there is a strong emphasis on testable hypotheses, empirical observation, supportable mechanisms and models, rigorous experimental methods, acceptable criteria of validation, and the like. Nonetheless, this approach to cognitive science does also raise a number of specific questions about the scope of amenable phenomena (e.g., meaning, consciousness, etc.) -- and it also raises questions of whether such a perspective requires an expansion of what is typically considered within the purview of scientific method (e.g., the role of the observer/scientist). (shrink)

Cognitive Science, Volume 46, Issue 9, September 2022.

Over the last few decades, our knowledge of how the human mind and brain works increased dramatically. The field of cognitive science enables us to understand religious traditions, rituals, and visionary experiences in novel ways. This has implications for the study of the New Testament and early Christianity. How people in the ancient Mediterranean world remembered sayings and stories, what they experienced when participating in rituals, how they thought about magic and miracle, and how they felt and reasoned (...) about moral questions--all of that can be now better understood with the help of insights from cognitive science. István Czachesz argues that the field of New Testament Studies witnesses the beginning of a cognitive turn. He surveys relevant developments in the Cognitive Science of Religion and explores the field of cognitive and behavioral sciences in search of opportunities of gaining new insights about biblical materials. Czachesz presents some methodological tools and initial steps, together with a large number of examples of applying the cognitive approach to the New Testament and related ancient literature. (shrink)

The view of embodied cognition believes that cognition is embodied in nature, only the dynamics involved in the interaction between cognitive activities and the nervous system, body and environment, only by closely linking the correct evaluation of time-dependent and relationship, then only can make a correct understanding of cognitive activities. The core concepts of body and environment involved in embodied cognition are different from the body and environment in the usual sense. In terms of research methods, dynamic (...) research methods that are different from traditional computer simulations are also adopted. The article first integrates and analyzes the basic position and general propositions in the discipline, then the embodied cognition are explained based on author's understanding. In addition, the suitability of dynamic research methods, its advantages and disadvantages is analyzed, and finally, a brief summary of the current status of embodied cognition research. (shrink)

It is often assumed that cognitive science is built upon folk psychology, and that challenges to folk psychology are therefore challenges to cognitive science itself. We argue that, in practice, cognitive science and folk psychology treat entirely non-overlapping domains: cognitive science considers aspects of mental life which do not depend on general knowledge, whereas folk psychology considers aspects of mental life which do depend on general knowledge. We back up our argument on (...) theoretical grounds, and also illustrate the separation between cognitive scientific and folk psychological phenomena in a number of cognitive domains. We consider the methodological and theoretical significance of our arguments for cognitive science research. (shrink)

The interdisciplinary field of cognitive science brings together elements of cognitive psychology, mathematics, perception, and linguistics. Focusing on the main areas of exploration in this field today, Cognitive Science presents comprehensive overviews of research findings and discusses new cross-over areas of interest. Contributors represent the most senior and well-established names in the field. This volume serves as a high-level introduction, with sufficient breadth to be a graduate-level text, and enough depth to be a valued (...) reference source to researchers. (shrink)

Cognitive science continues to make a compelling case for having a coherent, unique, and fundamental subject of inquiry: What is the nature of minds, where do they come from, and how do they work? Central to this inquiry is the notion of agents that have goals, one of which is their own persistence, who use dynamically constructed knowledge to act in the world to achieve those goals. An agentive perspective explains why a special class of systems have a (...) cluster of co‐occurring capacities that enable them to exhibit adaptive behavior in a complex environment: perception, attention, memory, representation, planning, and communication. As an intellectual endeavor, cognitive science may not have achieved a hard core of uncontested assumptions that Lakatos (1978) identifies as emblematic of a successful research program, but there are alternative conceptions according to which cognitive science has been successful. First, challenges of the early, core tenet of “Mind as Computation” have helped put cognitive science on a stronger foundation—one that incorporates relations between minds and their environments. Second, even if a full cross‐disciplinary theoretic consensus is elusive, cognitive science can inspire distant, deep, and transformative connections between pairs of fields. To be intellectually vital, cognitive science need not resemble a traditional discipline with its associated insularity and unchallenged assumptions. Instead, there is strength and resilience in the diverse perspectives and methods that cognitive science assembles together. This interdisciplinary enterprise is fragile and perhaps inherently unstable, as the looming absorption of cognitive science into psychology shows. Still, for many researchers, the excitement and benefits of triangulating on the nature of minds by integrating diverse cases cannot be secured by a stable discipline with an uncontested core of assumptions. (shrink)

Bayesian reverse-engineering is a research strategy for developing three-level explanations of behavior and cognition. Starting from a computational-level analysis of behavior and cognition as optimal probabilistic inference, Bayesian reverse-engineers apply numerous tweaks and heuristics to formulate testable hypotheses at the algorithmic and implementational levels. In so doing, they exploit recent technological advances in Bayesian artificial intelligence, machine learning, and statistics, but also consider established principles from cognitive psychology and neuroscience. Although these tweaks and heuristics are highly pragmatic in (...) character and are often deployed unsystematically, Bayesian reverse-engineering avoids several important worries that have been raised about the explanatory credentials of Bayesian cognitive science: the worry that the lower levels of analysis are being ignored altogether; the challenge that the mathematical models being developed are unfalsifiable; and the charge that the terms ‘optimal’ and ‘rational’ have lost their customary normative force. But while Bayesian reverse-engineering is therefore a viable and productive research strategy, it is also no fool-proof recipe for explanatory success. (shrink)

Cognitive science has been traditionally organized around the individual as the basic unit of cognition. Despite developments in areas such as communication, human–machine interaction, group behavior, and community organization, the individual-centric approach heavily dominates both cognitive research and its application. A promising direction for cognitive science is the study of augmented intelligence, or the way social and technological systems interact with and extend individual cognition. The cognitive science of augmented intelligence holds promise (...) in helping society tackle major real-world challenges that can only be discovered and solved by teams made of individuals and machines with complementary skills who can productively collaborate with each other. (shrink)

A scholarly examination of the centrality of the mind-body problem within and across the science of cognition--from philosophy to psychology to artificial intelligence to neural science. Conceptions of the mind-body problem range from the heritage of Cartesianism to the identification of the circumscribed brain structures responsible for domain specific cognitive mechanisms. Neither narrowly technical nor philosophically vague, this is a structured and detailed account of advancing intellectual developments in theory, research, and knowledge illumined by the conceptual (...) vicissitudes of the mind-body problem. This unique treatment will be of special interest to creative scholars in the disciplines of he sciences of cognition. (shrink)

Experimental philosophy has blossomed into a variety of philosophical fields including ethics, epistemology, metaphysics and philosophy of language. But there has been very little experimental philosophical research in the domain of philosophy of religion. Advances in Religion, Cognitive Science, and Experimental Philosophy demonstrates how cognitive science of religion has the methodological and conceptual resources to become a form of experimental philosophy of religion. Addressing a wide variety of empirical claims that are of interest to philosophers (...) and psychologists of religion, a team of psychologists and philosophers apply data from the psychology of religion to important problems in the philosophy of religion including the psychology of religious diversity; the psychology of substance dualism; the problem of evil and the relation between religious belief and empathy; and the cognitive science explaining the formation of intuitions that unwittingly guide philosophers of religion when formulating arguments. Bringing together authors and researchers who have made important contributions to interdisciplinary research on religion in the last decade, Advances in Religion, Cognitive Science, and Experimental Philosophy provides new ways of approaching core philosophical and psychological problems. (shrink)

Drawn sequences of images, like those in comics and picture stories, are a pervasive and fundamental way that humans have communicated for millennia. Yet, the study of visual narratives has only recently gained traction in Cognitive Science. Here we explore what has held back the study of the cognition of visual narratives, and why researchers should join in scholarship of this ubiquitous aspect of expression.

Cognitive Science is a promising field of research that deals with one of the most fundamental questions ever: how do beings know? However, despite the long and extensive tradition of the field it has not yet become an area of knowledge with scientific identity. This is primarily due to three reasons: the lack of boundaries in defining the object of study, i.e. cognition, the lack of a precise, robust and consistent scientific methodology and results, and the inner (...) problems derived from its interdisciplinary nature. This paper presents a background review, a theoretical frame and a humble reflection on these topics in order to arouse the internal debate among readers once more. (shrink)

Purpose: This, the second part of a two-part paper, describes how the concerns of enactive cognitive science have been realized in actual research: methodological issues, proposed explanatory mechanisms and models, some of the potential as both a theoretical and applied science, and several of the major open research questions. Findings: Despite some skepticism about "mechanisms" in constructivist literature, enactive cognitive science attempts to develop cognitive formalisms and models. Such techniques as feedback loops, (...) self-organization, autocatalytic networks, and dynamical systems modeling are used to develop alternatives to cognitivist models. A number of technical similarities are starting to emerge in the different models being proposed. Research Implications: The need to resolve the interplay between autonomy and coupling with the environment suggests the need for further technical research. And the reintroduction of first-person concerns into cognitive science raises some questions of method, particularly with regard to the relationship between first-person experience, neuroscience, and methods of description, analysis, and explanation. Results to date suggest that insights from enactive cognitive science could lead to innovations in the design of artifacts. (shrink)

The so-called ‘cognitive revolution’ (Gardner, 1985) in American psychology owed much to developments in adjacent disciplines, especially theoretical linguistics and computer science. Indeed, the cognitive revolution brought forth, not only a change in the conception of psychology, but also an inter-disciplinary approach to understanding the mind, involving philosophy, anthropology and neuroscience along with computer science, linguistics and psychology. Many commentators agree in dating the conception of this inter-disciplinary approach, cognitive science, to 11 September 1956, (...) the second day of a symposium on information theory held at MIT (Miller, 2003). Over the next twenty years or so, cognitive science developed an institutional presence through research centres, conferences, journals, and a substantial infusion of funds from the Alfred P. Sloan Foundation. (shrink)

This book presents the Proceedings of the Second International Colloquium on Cognitive Science, held at San Sebastian in May, 1991, to discuss from an interdisciplinary point of view topics which are at the intersection of philosophy and cognitive science. With a total of eleven papers from leading scholars in the field, the volume provides many different theoretical approaches to the study of Categories, Consciousness and Reasoning. The book is addressed to researchers, specialists, advanced students and scholars (...) in the fields of epistemology, philosophy of mind, psychology, semantics, logic and artificial intelligence. (shrink)

This chapter subsumes David Marr’s levels of analysis account of explanation in cognitive science under the framework of mechanistic explanation: Answering the questions that define each one of Marr’s three levels is tantamount to describing the component parts and operations of mechanisms, as well as their organization, behavior, and environmental context. By explicating these questions and showing how they are answered in several different cognitive science research programs, this chapter resolves some of the ambiguities that (...) remain in Marr’s account, and shows that many different areas and traditions of cognitive scientific research can be unified under the mechanistic framework. (shrink)

This is the first major textbook to offer a truly comprehensive review of cognitive science in its fullest sense. Ranging across artificial intelligence models and cognitive psychology through to recent discursive and cultural theories Rom Harre offers a breathtakingly original yet accessible integration of the field. At its core this textbook addresses the question "is psychology a science?" with a clear account of scientific method and explanation and their bearing on psychological research. A pivotal figure (...) in psychology and philosophy for many decades Rom Harre has turned his unmatched breadth of reference and insight for students at all levels. Whether describing, language, categorization, memory, the brain or connectionism the book always links our intuitions about beliefs, desires and their social context to the latest accounts of their place in computational and biological models. Fluently written and well structured, this an ideal text for students. The book is divided into four basic modules, with three lectures in each; the reader is guided with helpful learning points, study and essay questions and key readings for each chapter. (shrink)

The rise of cognitive neuroscience is the most important scientific and intellectual development of the last thirty years. Findings pour forth, and major initiatives for brain research continue. The social sciences have responded to this development slowly--for good reasons. The implications of particular controversial findings, such as the discovery of mirror neurons, have been ambiguous, controversial within neuroscience itself, and difficult to integrate with conventional social science. Yet many of these findings, such as those of experimental neuro-economics, (...) pose very direct challenges to standard social science. At the same time, however, the known facts of social science, for example about linguistic and moral diversity, pose a significant challenge to standard neuroscience approaches, which tend to focus on "universal" aspects of human and animal cognition. A serious encounter between cognitive neuroscience and social science is likely to be challenging, and transformative, for both parties. Although a literature has developed on proposals to integrate neuroscience and social science, these proposals go in divergent directions. None of them has a developed conception of social life. This book surveys these issues, introduces the basic alternative conceptions both of the mental world and the social world, and show how, with sufficient modification, they can be fit together in plausible ways. The book is not a "new theory " of anything, but rather an exploration of the critical issues that relate to the social aspects of cognition which expands the topic from the social neuroscience of immediate interpersonal interaction to the whole range of places where social variation interacts with the cognitive. The focus is on the conceptual problems produced by any attempt to take these issues seriously, and also on the new resources and considerations relevant to doing so. But it is also on the need for a revision of social theoretical concepts in order to utilize these resources. The book points to some conclusions, especially about how the process of what was known as socialization needs to be understood in cognitive science friendly terms. But there is no attempt to resolve the underlying issues within cognitive science, which will doubtless persist. (shrink)

Cognitive science is a cross-disciplinary enterprise devoted to understanding the nature of the mind. In recent years, investigators in philosophy, psychology, the neurosciences, artificial intelligence, and a host of other disciplines have come to appreciate how much they can learn from one another about the various dimensions of cognition. The result has been the emergence of one of the most exciting and fruitful areas of inter-disciplinary research in the history of science. This volume of original essays (...) surveys foundational, theoretical, and philosophical issues across the discipline, and introduces the foundations of cognitive science, the principal areas of research, and the major research programs. With a focus on broad philosophical themes rather than detailed technical issues, the volume will be valuable not only to cognitive scientists and philosophers of cognitive science, but also to those in other disciplines looking for an authoritative and up-to-date introduction to the field. (shrink)

About 30 years ago, the Dynamical Hypothesis instigated a variety of insights and transformations in cognitive science. One of them was the simple observation that, quite unlike trial-based tasks in a laboratory, natural ecologically valid behaviors almost never have context-free starting points. Instead, they produce lengthy time series data that can be recorded with dense-sampling measures, such as heartrate, eye movements, EEG, etc. That emphasis on studying the temporal dynamics of extended behaviors may have been the trigger that (...) led to a rethinking of what a “representation” is, and then of what a “cognitive agent” is. This most recent and perhaps most revolutionary transformation is the idea that a cognitive agent need not be a singular physiological organism. Perhaps a group of organisms, such as several people working on a joint task, can temporarily function as one cognitive agent – at least while they're working adaptively and successfully. (shrink)

Bayesian cognitive science is a research programme that relies on modelling resources from Bayesian statistics for studying and understanding mind, brain, and behaviour. Conceiving of mental capacities as computing solutions to inductive problems, Bayesian cognitive scientists develop probabilistic models of mental capacities and evaluate their adequacy based on behavioural and neural data generated by humans (or other cognitive agents) performing a pertinent task. The overarching goal is to identify the mathematical principles, algorithmic procedures, and causal (...) mechanisms that enable cognitive agents to take uncertainty into account and weigh it appropriately in producing adaptive behaviour. -/- The appeal of Bayesian cognitive science derives from its transparency, normativity, and unifying power. Resources from Bayesian statistics allow cognitive scientists to characterise transparently, in terms of random variables and probabilistic dependencies between them, the inductive problems that many mental capacities are presumed to solve. Given this characterisation, researchers can define an upper bound on one’s performance on that problem and use it as a benchmark for interpreting experimental results, formulating hypotheses about why and when deviations from optimal performance should be expected, and seeking explanations of mental capacities within one encompassing theoretical framework. -/- Although critics question the testability, explanatory power, and plausibility of Bayesian models of mental capacities, Bayesian cognitive science has proved itself to be an incredibly fruitful research programme. Fuelled by empirical and theoretical results from psychology, neuroscience, philosophy, computer science, artificial intelligence, and evolution, Bayesian cognitive science has: advanced our understanding of why cognitive systems should keep track of uncertainty and use it to facilitate adaptive behaviour; clarified how the brain might encode information about the uncertainty of its stimuli and perform computations with probability distributions; and crystallised the insight that cognitive agents’ management of uncertainty might be grounded in predictive processes aimed at avoiding surprising exchanges with the environment. (shrink)

Cognitive Science combines the interdisciplinary streams of cognitive science into a unified narrative in an all-encompassing introduction to the field. This text presents cognitive science as a discipline in its own right, and teaches students to apply the techniques and theories of the cognitive scientist's 'toolkit' - the vast range of methods and tools that cognitive scientists use to study the mind. Thematically organized, rather than by separate disciplines, Cognitive Science (...) underscores the problems and solutions of cognitive science, rather than those of the subjects that contribute to it - psychology, neuroscience, linguistics, etc. The generous use of examples, illustrations, and applications demonstrates how theory is applied to unlock the mysteries of the human mind. Drawing upon cutting-edge research, the text has been updated and enhanced to incorporate new studies and key experiments since the first edition. A new chapter on consciousness has also been added. (shrink)

Cognitive science is an interdisciplinary research endeavor focusing on human cognitive phenomena such as memory, language use, and reasoning. It emerged in the second half of the 20th century and is charting new directions at the beginning of the 21st century. This chapter begins by identifying the disciplines that contribute to cognitive science and reviewing the history of the interdisciplinary engagements that characterize it. The second section examines the role that mechanistic explanation plays in (...) cognitive science, while the third focuses on the importance of mental representations in specifically cognitive explanations. The fourth section considers the interdisciplinary nature of cognitive science and explores how multiple disciplines can contribute to explanations that exceed what any single discipline might accomplish. The conclusion sketches some recent developments in cognitive science and their implications for philosophers. (shrink)

Games are more varied and occupy more of daily life than ever before. At the same time, the tools available to study game play and players are more powerful than ever, especially massive data sets from online platforms and computational engines that can accurately evaluate human decisions. This essay offers six suggestions for future cognitive science research on games: Don't forget about chess, Look beyond action games and chess, Use -optimal play to understand human play and players, (...) Investigate social phenomena, Raise the standards for studies of games as treatments, Talk to real experts. (shrink)

How can we think about things in the outside world? There is still no widely accepted theory of how mental representations get their meaning. In light of pioneering research, Nicholas Shea develops a naturalistic account of the nature of mental representation with a firm focus on the subpersonal representations that pervade the cognitive sciences.

Cognitive science is, of course, not really a new discipline, but a recognition of a fundamental set of common concerns shared by the disciplines of psychology, computer science, linguistics, economics, epistemology, and the social sciences generally. All of these disciplines are concerned with information processing systems, and all of them are concerned with systems that are adaptive—that are what they are from being ground between the nether millstone of their physiology or hardware, as the case may be, (...) and the upper millstone of a complex environment in which they exist. Systems that are adaptive may equally well be described as “artificial,” for as environments change, they can be expected to change too, as though they were deliberately designed to fit those environments (as indeed they sometimes are).The task of empirical science is to discover and verify invariants in the phenomena under study. The artificiality of information processing systems creates a subtle problem in defining empirical invariants in such systems. For observed regularities are very likely invariant only within a limited range of variation in their environments, and any accurate statement of the laws of such systems must contain reference to their relativity to environmental features. It is a common experience in experimental psychology, for example, to discover that we are studying sociology—the effects of the past histories of our subjects—when we think we are studying physiology—the effects of properties of the human nervous system. Similarly, business cycle economists are only now becoming aware of the extent to which the parameters of the system they are studying are dependent on the experiences of a population with economic events over the previous generation.In artificial sciences, the descriptive and the normative are never far apart. Thus, in economics, the “principle of rationality” is sometimes asserted as a descriptive invariant, sometimes as advice to decision makers. Similarly, in psychology, the processes of adaptation (learning) have always been a central topic, at one time a topic that dominated the whole field of research. Linguistics, too, has suffered its confusions between descriptive and normative attitudes towards its subject. But we must avoid the error, in studying information processing systems, of thinking that the adaptive processes themselves must be invariant; and we must be prepared to face the complexities of regression in the possibility that they themselves may be subject to improvement and adaptation.It might have been necessary a decade ago to argue for the commonality of the information processes that are employed by such disparate systems as computers and human nervous systems. The evidence for that commonality is now overwhelming, and the remaining questions about the boundaries of cognitive science have more to do with whether there also exist nontrivial commonalities with information processing in genetic systems than with whether men and machines both think. (shrink)

Paul Thagard has recently argued that thought experiments are dangerous and misleading when we try to use them as evidence for claims. This paper refutes his skepticism. Building on Thagard’s own work in cognitive science, I suggest that Thagard has much that is positive to say about how thought experiments work. My last section presents some new directions for research on the intersection between thought experiments and cognitive science.

As the pluralization in the title of MITECS suggests, and as many reviewers have noted, the stance that we adopted as general editors for this project was ecumenical. We were particularly concerned to generate a volume whose range of topics and perspectives indicated that “cognitive science” was different things to different groups of researchers, and that many even fundamental questions remain open after at least four decades of various interdisciplinary ventures. Implicit in this view is a wariness of (...) any putative magic key to understanding the complexities of cognition in all of its diversity, and the hope that by providing a forum in which this range of work could be reviewed by anyone with time and inclination, the field as a whole would be better positioned to reflect on its future directions. Readers of the preceding reviews might be interested in a few words about the development of the project. Contracted in the early summer of 1995, MITECS began as a volume projected at half of its eventual size, but with roughly the same scope it has in published form. The general editors, Frank Keil and myself, had been thinking about a volume of this sort independently over the preceding year or so, and so much of the structure of the volume was already outlined by mid-1995. Thus, we were able to move relatively quickly in the second half of 1995 to assemble a team of 9 advisory editors for the six sections that constitute the organization of the volume; as reviewers have noted, the presence of these sections in the print version is manifest primarily by the six overview essays that occupy the first 100 or so pages in MITECS. (shrink)

In recent decades, a new scientific approach to understand, explain, and predict many features of religion has emerged. The cognitive science of religion has amassed research on the forces that shape the tendency for humans to be religious and on what forms belief takes. It suggests that religion, like language or music, naturally emerges in humans with tractable similarities. This new approach has profound implications for how we understand religion, including why it appears so easily, and why (...) people are willing to fight-and die for it. Yet it is not without its critics, and some fear that scholars are explaining the ineffable mystery of religion away, or by showing that religion is natural proves or disproves the existence of God. An Introduction to the Cognitive Science of Religion offers students and general readers an accessible introduction to the approach, providing an overview of key findings and the debates that shape it. The volume includes a glossary of key terms, and each chapter includes suggestions for further thought and further reading as well as chapter summaries highlighting key points. This book is an indispensable resource for introductory courses on religion and a much-needed option for advanced courses. (shrink)

Marr’s seminal distinction between computational, algorithmic, and implementational levels of analysis has inspired research in cognitive science for more than 30 years. According to a widely-used paradigm, the modelling of cognitive processes should mainly operate on the computational level and be targeted at the idealised competence, rather than the actual performance of cognisers in a specific domain. In this paper, we explore how this paradigm can be adopted and revised to understand mathematical problem solving. The computational-level (...) approach applies methods from computational complexity theory and focuses on optimal strategies for completing cognitive tasks. However, human cognitive capacities in mathematical problem solving are essentially characterised by processes that are computationally sub-optimal, because they initially add to the computational complexity of the solutions. Yet, these solutions can be optimal for human cognisers given the acquisition and enactment of mathematical practices. Here we present diagrams and the spatial manipulation of symbols as two examples of problem solving strategies that can be computationally sub-optimal but humanly optimal. These aspects need to be taken into account when analysing competence in mathematical problem solving. Empirically informed considerations on enculturation can help identify, explore, and model the cognitive processes involved in problem solving tasks. The enculturation account of mathematical problem solving strongly suggests that computational-level analyses need to be complemented by considerations on the algorithmic and implementational levels. The emerging research strategy can help develop algorithms that model what we call enculturated cognitive optimality in an empirically plausible and ecologically valid way. (shrink)

This paper surveys applications of logical methods in the cognitive sciences. Special attention is paid to non-monotonic logics and complexity theory. We argue that these particular tools have been useful in clarifying the debate between symbolic and connectionist models of cognition.

According to the “Embodied Cognition” entry in the Stanford Encyclopedia of Philosophy, the three landmark texts in the 4E cognitive science tradition are Lakoff and Johnson’s Metaphors We Live By, Varela, Thompson, and Rosch’s The Embodied Mind, and Andy Clark’s Being There. In my first section, I offer a phenomenological interpretation of these three texts, identifying recuring affirmations of the figure of dance alongside explicit marginalization of the practice of dance, perhaps in part due to cognitive (...) class='Hi'>science’s overemphasis on cognition to the exclusion of affect. In my second section, drawing on my previous interpretations of proto-affect theorists (including Spinoza, Deleuze, and Fanon), I channel this tension in 4E cognitive science into a dancing partnership with human science psychology, suggesting three “choreographic provocations” for therapeutic practice and psychological research, namely (1) treating clients/subjects as dancers, (2) reimagining research and therapy as improvised duets between practitioners and clients/subjects, and (3) pursuing an ideal of freer movement and an emergent flourishing singularity for clients/subjects. Finally, I reformulate these three choreographic provocations in terms of my new theoretical method of “dancing-with,” as well as the four psychological prerequisites for flourishing posited by my figuration philosophy of dance. (shrink)

Cognitive science is an interdisciplinary conglomerate of various research fields and disciplines, which increases the risk of fragmentation of cognitive theories. However, while most previous work has focused on theoretical integration, some kinds of integration may turn out to be monstrous, or result in superficially lumped and unrelated bodies of knowledge. In this paper, I distinguish theoretical integration from theoretical unification, and propose some analyses of theoretical unification dimensions. Moreover, two research strategies that are supposed (...) to lead to unification are analyzed in terms of the mechanistic account of explanation. Finally, I argue that theoretical unification is not an absolute requirement from the mechanistic perspective, and that strategies aiming at unification may be premature in fields where there are multiple conflicting explanatory models. (shrink)

Philosophers of music (and also music theorists) have recognized for a long time that research in the sciences, especially psychology, might have import for their own work. (Langer 1941 and Meyer 1956 are good examples.) However, while scientists had been interested in music as a subject of research (e.g., Helmholtz 1912, Seashore 1938), the discipline known as psychology of music, or more broadly cognitive science of music, came into its own only around 1980 with the publication (...) of several landmark works. Among the most important of these were The Psychol- ogy of Music (1980), a collection of papers edited by the psychologist Diana Deutsch, and A Generative Theory of Tonal Music (1983) by music theorist and composer Fred Lerdahl and linguist Ray Jackendoff. These works and others made possible the first attempts to apply scientific research to philosophical issues concerning music (e.g., Raffman 1993, DeBellis 1995). Since the 1980’s, of course, a great deal of research has been done in cognitive science, philosophy, and music. For philosophers, there are perhaps three topics with respect to which findings in the cognitive sciences are most likely to be germane—the nature of musical understanding, the role of emotions or feelings in music, and the evaluation of musical works. This brief overview will describe some of the scientific research that has been done on these topics, and then indicate how it might be philosophically significant. (shrink)

Computational modeling of sketch understanding is interesting both scientifically and for creating systems that interact with people more naturally. Scientifically, understanding sketches requires modeling aspects of visual processing, spatial representations, and conceptual knowledge in an integrated way. Software that can understand sketches is starting to be used in classrooms, and it could have a potentially revolutionary impact as the models and technologies become more advanced. This paper looks at one such effort, Sketch Worksheets, which have been used in multiple classroom (...) experiments already, with students ranging from elementary school to college. Sketch Worksheets are a software equivalent of pencil and paper worksheets commonly found in classrooms, but they provide on-the-spot feedback based on what students draw. They are built on the CogSketch platform, which provides qualitative visual and spatial representations and analogical processing based on computational models of human cognition. This paper explores three issues. First, we examine how research from cognitive science and artificial intelligence, combined with the constraints of creating new kinds of educational software, led to the representations and processing in CogSketch. Second, we examine how these capabilities have been used in Sketch Worksheets, drawing upon experiments with fifth-grade students in biology and college students in engineering design and in geoscience. Finally, we examine some open issues in sketch understanding that need to be addressed to better model high-level aspects of vision, and for sketch understanding systems to reach their full potential for supporting education. (shrink)

I sketch an explanatory framework that fits a variety of contemporary research programs in cognitive science. I then investigate the scope and the implications of this framework. The framework emphasizes (a) the explanatory role played by the semantic content of cognitive representations, and (b) the important mechanistic, non-intentional dimension of cognitive explanations. I show how both of these features are present simultaneously in certain varieties of cognitive explanation. I also consider the explanatory role played (...) by grounded representational content, that is, content evaluated by appeal to its truth, falsity, accuracy, inaccuracy and other relational properties. (shrink)

Alongside significant gains in our understanding of the human mind, research in Cognitive Science has produced substantial evidence that the details of cognitive processes vary across cultures, contexts, and individuals. In order to arrive at a more nuanced account of the workings of the human mind, in this letter we argue that one challenge for the future of Cognitive Science is the integration of this evidence of variation with findings which can be generalized.

This book is intended as an introduction to the breadth of current research in cognitive science, with the research at Lund University Cognitive Science as our sample. The result is a smorgasbord for readers with some background in the neighbouring disciplines. Through the chapters we will follow some of the important cross-disciplinary issues in cognitive science. One is how the external world is represented, from cognitive maps in rats, to drawings made (...) to enhance communication, or the organization of semantic knowledge. Another is to what extent such representations really are used: the world is often its own best model in areas from robotics to choice, and several chapters illustrate that even communication is firmly situated in and constrained by its surroundings. In addition, many chapters emphasize the essentially dynamic relationship between mind and environment, in areas from development to interaction and learning. A third thread is how research concerning other animals= cognitive capacities, from pigeons to chimpanzees, has inspired research on human cognition, and how this comparative approach can be made to incorporate also non-animate fellow beings, such as robots and virtual characters. In sum, the book contains most of the areas we think are important in cognitive science today, and we hope that it will be of use for beginning researchers and advanced students in the area. Its production is part of the celebrations of Lund University Cognitive Science’s 20th anniversary. Our group hosts researchers with backgrounds in psychology, philosophy, computer science, linguistics, computational neuroscience, education, etc., and all of us have a multidisciplinary education. We encourage you to visit our web pages at www.lucs.lu.se to learn more about the activities of the group. (shrink)

In this chapter, the author considers a line of thought in Arthur Danto in that regard about the bearing of cognitive science on our construal of changes in art. For Danto, a key to the issue of how to understand change in art forms and artistic identities is found in his fundamental notion that both the meaning and the style of a work of art are historically indexed; that is, they depend on historical conditions. Danto's skepticism about facile (...) changes in world views is born out of his theory that the history of such changes has certain logic, defined over basic or fundamental forms of action and thought; a view that applies as much to science as it does to art. The author's claim has been that recent research shows that, logical deductions aside, advances in cognitive science suggest that the language of art criticism will have to change. (shrink)

Attempts to apply the mathematical tools of dynamical systems theory to cognition in a systematic way has been well under way since the early 90s and has been recognised as a “third contender” to computationalist and connectionist approaches :441–463, 1996). Nevertheless, it was also realised that such an application will not lead to a solid paradigm as straightforwardly as was initially hoped. In this paper I explicate a method for assessing such proposals by drawing upon Lakatos’s Criticism and the growth (...) of knowledge, Cambridge University Press, London, pp 91–195, 1970) methodology of scientific research programs. MSRP focuses on the heuristics of a particular field and gauges the model/theory building stratagems by reference to theoretical and empirical progress, on the one hand, and the continuity and the autonomy of the way the field’s heuristic generates its series of models/theories, on the other. The requirement of continuity and autonomy afford distinct senses of ad hoc-ness, which serve as an effective tool to detect various subtleties which may otherwise be missed: the present approach identifies shortcomings missed by Chemero’s radical embodied cognitive science and falsifies Chemero’s claim that the methodological powers of his model-based account is on a par with computationalism. In general, I claim that MSRP is relevant to current methodological issues in cognitive science and can supplement debates regarding “local” assessments of methodologies, such as that between mechanical versus covering-law explanations. MSRP must at least be viewed as a necessary constraint for any methodological considerations in cognitive science. (shrink)

From a religious studies perspective, Atran & Norenzayan (A&N) succeed in arguing for the influence of evolved cognitive functions in religious phenomena. To develop their argument further, four suggestions are offered: (1) Look beyond the ordinary to the extraordinary; (2) culture matters more than ever; (3) theists need not despair, atheists ought not celebrate; and (4) dreaming is a primal wellspring of religion.

Beller, Bender, and Medin (this issue) offer a provocative proposal outlining several reasons why anthropology and the rest of cognitive science might consider parting ways. Among those reasons, they suggest that separation might maintain the diversity needed to address larger problems facing humanity, and that the research strategies used across the disciplines are already so diverse as to be incommensurate. The present paper challenges the view that research strategies are incommensurate and offers a multimethod approach to (...) cultural research that can help to establish common ground while maintaining diversity. (shrink)

According to the dominant computational approach in cognitive science, cognitive agents are digital computers; according to the alternative approach, they are dynamical systems. This target article attempts to articulate and support the dynamical hypothesis. The dynamical hypothesis has two major components: the nature hypothesis (cognitive agents are dynamical systems) and the knowledge hypothesis (cognitive agents can be understood dynamically). A wide range of objections to this hypothesis can be rebutted. The conclusion is that cognitive (...) systems may well be dynamical systems, and only sustained empirical research in cognitive science will determine the extent to which that is true. (shrink)

The article chronicles the different panels devoted tothe cognitive science of religion at the meeting of the Society for the Scientific Study of Religion (SSSR) in Tampa, Florida, in November 2007. The aim is to verify the state of this subdiscipline and to check how much this work-in-progress affects the present state of the dialogue between science and religion. Several signs point to a positive development in this scientific branch and favor a sound reception in theology, which (...) should not ignore the new research. (shrink)