In recent attempts to characterize the cognitive mechanisms underlying altruistic motivation, one central question is the extent to which the capacity for altruism depends on the capacity for understanding other minds, or ‘mindreading’. Some theorists maintain that the capacity for altruism is independent of any capacity for mindreading; others maintain that the capacity for altruism depends on fairly sophisticated mindreading skills. I argue that none of the prevailing accounts is adequate. Rather, I argue that altruistic motivation depends on a (...) basic affective system, a ‘Concern Mechanism’, which requires only a minimal capacity for mindreading. (shrink)

Recent theorists suggest that our capacity to respond affectively to fictions depends on our ability to engage in simulation: either simulating a character in the fiction, or simulating someone reading or watching the fiction as though it were fact. We argue that such accounts are quite successful at accounting for many of the basic explananda of our affective engagements in fiction. Nonetheless, we argue further that simulationist accounts ultimately fail, for simulation involves an ineliminably ego-centred element that is atypical (...) of our experience of fiction. We then draw on recent work in philosophical psychology to articulate a more psychologically plausible account of our emotional engagement with fiction. (shrink)

This paper discusses essential motivational representations necessary for a comprehensive computational cognitive architecture. It hypothesizes the need for implicit drive representations, as well as explicit goal representations. Drive representations consist of primary drives — both low-level primary drives (concerned mostly with basic physiological needs) and high-level primary drives (concerned more with social needs), as well as derived (secondary) drives. On the basis of drives, explicit goals may be generated on the fly during an agent’s interaction with various (...) situations. These motivational representations help to make cognitive architectural models more comprehensive and provide deeper explanations of psychological processes. This work represents a step forward in making computational cognitive architectures better reflections of the human mind and all its motivational complexity and intricacy. (shrink)

Visual Search without Selective Attention calls into question the necessity of a covert selective attention mechanism by implementing a formal model that includes basic visual mechanisms, saccades, and simple task strategies. Across three search tasks, the model accounts for response times as well as the proportion of errors observed in human participants, including effects of item crowding in the visual stimulus.

I intend to show some of the limits of the decision-theoretic model in connection with the analysis of cognitive agency. Although the concept of maximum expected utility can be helpful for explaining the decision-making process, it is certainly not the primary motor that moves agents to action. Moreover, it has been noticed elsewhere that this model is inadequate to the analysis of single cases of practical reasoning. A theory is proposed that introduces a plan-structure as a basic idea. (...) In order to know its very conceptual scope, we need to accommodate that theory to a cognitive architecture whereby the rational and autonomous agent makes choices and deliberates between courses of action to achieve specific goals that are of its interest. The paper endeavours also to clarify the relationship between the different modules that should constitute the architecture of an agent to accomplish the requisites of efficiency and autonomy in a changeable and dynamic world. (shrink)

Much of our everyday, embodied action comes in the form of smooth coping. Smooth coping is skillful action that has become habituated and ingrained, generally placing less stress on cognitive load than considered and deliberative thought and action. When performed with skill and expertise, walking, driving, skiing, musical performances, and short-order cooking are all examples of the phenomenon. Smooth coping is characterized by its rapidity and relative lack of reflection, both being hallmarks of automatization. Deliberative and reflective actions provide (...) the contrast case. In Dreyfus’ classic view, smooth coping is “mindless” absorption into action, being in the flow, and any reflective thought will only interrupt this flow. Building on the pragmatist account of Dewey, others, such as Sutton, Montero, and Gallagher, insist on the intelligent flexibility built into smooth coping, suggesting that it is not equivalent to automatization. We seek to answer two complementary challenges in this article. First, how might we model smooth coping in autonomous agents at fine granularity? Second, we use this model of smooth coping to show how we might implement smooth coping in artificial intelligent agents. We develop a conceptual model of smooth coping in LIDA. LIDA is an embodied cognitive architecture implementing the global workspace theory of consciousness, among other psychological theories. LIDA’s implementation of consciousness enables us to account for the phenomenology of smooth coping, something that few cognitive architectures would be able to do. Through the fine granular analysis of LIDA, we argue that smooth coping is a sequence of automatized actions intermittently interspersed with consciously mediated action selection, supplemented by dorsal stream processes. In other words, non-conscious, automatized actions often require occasional bursts of conscious cognition to achieve the skillful and flexible adjustments of smooth coping. In addition, never-conscious dorsal stream information and associated sensorimotor processes provide further online adjustments during smooth coping. To achieve smooth coping in LIDA we introduce a new module to the LIDA cognitive architecture the Automatized Action Selection sub-module. Our complex model of smooth coping borrows notions of “embodied intelligence” from enactivism and augments these by allowing representations and more detailed mechanisms of conscious control. We explore several extended examples of smooth coping, starting from basic activities like walking and scaling up to more complex tasks like driving and short-order cooking. (shrink)

In the late 1980s, there were many who heralded the emergence of connectionism as a new paradigm – one which would eventually displace the classically symbolic methods then dominant in AI and Cognitive Science. At present, there remain influential connectionists who continue to defend connectionism as a more realistic paradigm for modeling cognition, at all levels of abstraction, than the classical methods of AI. Not infrequently, one encounters arguments along these lines: given what we know about neurophysiology, it is (...) just not plausible to suppose that our brains are digital computers. Thus, they could not support a classical architecture. I argue here for a middle ground between connectionism and classicism. I assume, for argument's sake, that some form(s) of connectionism can provide reasonably approximate models – at least for lower-level cognitive processes. Given this assumption, I argue on theoretical and empirical grounds that most human mental skills must reside in separate connectionist modules or sub-networks. Ultimately, it is argued that the basic tenets of connectionism, in conjunction with the fact that humans often employ novel combinations of skill modules in rule following and problem solving, lead to the plausible conclusion that, in certain domains, high level cognition requires some form of classical architecture. During the course of argument, it emerges that only an architecture with classical structure could support the novel patterns of information flow and interaction that would exist among the relevant set of modules. Such a classical architecture might very well reside in the abstract levels of a hybrid system whose lower-level modules are purely connectionist. (shrink)

The paper provisionally accepts the goal of Goldman's primary epistemics, which is to seek reliability values for basic cognitive processes, and questions whether such values may plausibly be expected. The reliability of such processes as perception and memory is dependent on other aspects of cognitive structure, and especially on one's "conceptual scheme," the evaluation of which goes beyond primary epistemics (and its dependence on cognitive science) to social epistemics, or indeed to traditional epistemology and philosophy of (...) science. Two general arguments against the plausibility of determining reliability values for the basic cognitive architecture of humans are proposed, one applying Fodor's distinction between input and central systems, and the other invoking a point by Geertz about culture and evolution. Social epistemics is only briefly evaluated, as it is nascent. (shrink)

This book introduces an account of cognitive architecture, Cognitive Pluralism, on which the basic units of understanding are models of particular content domains. Having many mental models is a good adaptive strategy for cognition, but models can be incompatible with one another, leading to paradoxes and inconsistencies of belief, and it may not be possible to integrate the understanding supplied by multiple models into a comprehensive and self-consistent "super model". The book applies the theory to explaining (...) intuitive reasoning and cognitive illusions and explores implications for epistemology, semantics, and disunity of science. (shrink)

This book is a comprehensive development and defense of one of the guiding assumptions of evolutionary psychology: that the human mind is composed of a large number of semi-independent modules. The Architecture of the Mind has three main goals. One is to argue for massive mental modularity. Another is to answer a 'How possibly?' challenge to any such approach. The first part of the book lays out the positive case supporting massive modularity. It also outlines how the thesis should (...) best be developed, and articulates the notion of 'module' that is in question. Then the second part of the book takes up the challenge of explaining how the sorts of flexibility and creativity that are distinctive of the human mind could possibly be grounded in the operations of a massive number of modules.Peter Carruthers's third aim is to show how the various components of the mind are likely to be linked and interact with one another - indeed, this is crucial to demonstrating how the human mind, together with its familiar capacities, can be underpinned by a massively modular set of mechanisms. He outlines and defends the basic framework of a perception / belief / desire / planning / motor-control architecture, as well as detailing the likely components and their modes of connectivity. Many specific claims about the place within this architecture of natural language, of a mind-reading system, and others are explained and motivated. A number of novel proposals are made in the course of these discussions, one of which is that creative human thought depends upon a prior kind of creativity of action.Written with unusual clarity and directness, and surveying an extensive range of research in cognitive science, this book will be essential reading for anyone with an interest in the nature and organization of the mind. (shrink)

Recent accounts of pretense have been underdescribed in a number of ways. In this paper, we present a much more explicit cognitive account of pretense. We begin by describing a number of real examples of pretense in children and adults. These examples bring out several features of pretense that any adequate theory of pretense must accommodate, and we use these features to develop our theory of pretense. On our theory, pretense representations are contained in a separate mental workspace, a (...) Possible World Box which is part of the basic architecture of the human mind. The representations in the Possible World Box can have the same content as beliefs. Indeed, we suggest that pretense representations are in the same representational ``code'' as beliefs and that the representations in the Possible World Box are processed by the same inference and UpDating mechanisms that operate over real beliefs. Our model also posits a Script Elaborator which is implicated in the embellishment that occurs in pretense. Finally, we claim that the behavior that is seen in pretend play is motivated not from a ``pretend desire'', but from a real desire to act in a way that ®ts the description being constructed in the Possible World Box. We maintain that this account can accommodate the central features of pretense exhibited in the examples of pretense, and we argue that the alternative accounts either can't accommodate or fail to address entirely some of the central features of pretense. q 2000 Elsevier Science B.V. All rights reserved. (shrink)

Cognitive Iconology is a new theory of the relation of psychology to art. Instead of being an application of psychological principles, it is a methodologically aware account of psychology, art and the nature of explanation. Rather than fight over biology or culture, it shows how they must fit together. The term “cognitive iconology” is meant to mirror other disciplines like cognitive poetics and musicology but the fear that images must be somehow transparent to understanding is calmed by (...) the stratified approach to explanation that is outlined. In the book, cognitive iconology is a theory of cognitive tendencies that contribute to but are not determinative of an artistic meaning. At the center of the book are three case studies: images depicted within images, basic corrections to architectural renderings in images, and murals and paintings seen from the side. In all cases, there is a primitive perceptual pull that contribute to but do not override larger cultural meaning. The book then moves beyond the confines of the image to behavior around the image, and then ends with the concluding question of why some images are harder to understand than others. Cognitive Iconology promises to be important because it moves beyond the turf battles typically fought in image studies. It argues for a sustainable practice of interpretation that can live with other disciplines. Ian Verstegen is an art writer and historian living in Philadelphia. He is the author of Arnheim, Gestalt and Art (2005) and A Realist Theory of Art History (2012). (shrink)

It is often argued that human emotions, and the cognitions that accompany them, involve refinements of, and extensions to, more basic functionality shared with other species. Such refinements may rely on common or on distinct processes and representations. Multi-level theories of cognition and affect make distinctions between qualitatively different types of representations often dealing with bodily, affective and cognitive attributes of self-related meanings. This paper will adopt a particular multi-level perspective on mental architecture and show how a (...) mechanism of subsystem differentiation could have allowed an evolutionarily “old” role for emotion in the control of action to have altered into one more closely coupled to meaning systems. We conclude by outlining some illustrative consequences of our analysis that might usefully be addressed in research in comparative psychology, cognitive archaeology, and in laboratory research on memory for emotional material. (shrink)

Summarizes and illuminates two decades of research Gathering important papers by both philosophers and scientists, this collection illuminates the central themes that have arisen during the last two decades of work on the conceptual foundations of artificial intelligence and cognitive science. Each volume begins with a comprehensive introduction that places the coverage in a broader perspective and links it with material in the companion volumes. The collection is of interest in many disciplines including computer science, linguistics, biology, information science, (...) psychology, neuroscience, iconography, and philosophy. Examines initial efforts and the latest controversies The topics covered range from the bedrock assumptions of the computational approach to understanding the mind, to the more recent debates concerning cognitive architectures, all the way to the latest developments in robotics, artificial life, and dynamical systems theory. The collection first examines the lineageof major research programs, beginning with the basic idea of machine intelligence itself, then focuses on specific aspects of thought and intelligence, highlighting the much-discussed issue of consciousness, the equally important, but less densely researched issue of emotional response, and the more traditionally philosophical topic of language and meaning. Provides a gamut of perspectives The editors have included several articles that challenge crucial elements of the familiar research program of cognitive science, as well as important writings whose previous circulation has been limited. Within each volume the papers are organized to reflect a variety of research programs and issues. The substantive introductions that accompany each volume further organize the material and provide readers with a working sense of the issues and the connection between articles. (shrink)

This article presents a systematic exposition of how the basic ideas of Construction Grammar and the Parallel Architecture of grammar provide the framework for a proper account of morphological phenomena, in particular word formation. This framework is referred to as Construction Morphology. As to the implications of CxM for the architecture of grammar, the article provides evidence against a split between lexicon and grammar, in line with CxG. In addition, it shows that the PA approach makes it (...) possible to be explicit about what happens on which level of the grammar, and thus to give an insightful account of interface phenomena. These interface phenomena appear to require that various types of information are accessible simultaneously, and it is argued that constructional schemas have the right format for expressing these mutual dependencies between different types of information. (shrink)

A half-century ago the Dutch architect Aldo van Eyck encouraged designers to think about “space and time” not as abstractions in themselves but rather as cultural events better approached through the medium of “place and occasion.” Van Eyck made this point on the basis of his own travels and through his extensive readings in cultural anthropology, and his prescience is only now acquiring the credibility that it deserves through the work of a multitude of interdisciplinary researchers. Phenomenologists argue that we (...) are embodied organisms-acting-within-environments, and these inhabiting abodes are constructed of both material and cultural dimensions. We are thus preeminently social in our range of self-consciousness, and intensely ceremonial in every facet of our being. Evolutionary psychologists and anthropologists are currently locating the origin and development of our most basic social behaviors far in our pre-human past; neuroscientists are today modeling our social circuits in the deepest reaches of our brains. Architecture would gain much from an updated cultural theory grounded in these new models of human existence. (shrink)

Living systems employ several mechanisms and behaviors to achieve robustness and maintain themselves under changing internal and external conditions. Regulation stands out from them as a specific form of higher-order control, exerted over the basic regime responsible for the production and maintenance of the organism, and provides the system with the capacity to act on its own constitutive dynamics. It consists in the capability to selectively shift between different available regimes of self-production and self-maintenance in response to specific signals (...) and perturbations, due to the action of a dedicated subsystem which is operationally distinct from the regulated ones. The role of regulation, however, is not exhausted by its contribution to maintain a living system’s viability. While enhancing robustness, regulatory mechanisms play a fundamental role in the realization of an autonomous biological organization. Specifically, they are at the basis of the remarkable integration of biological systems, insofar as they coordinate and modulate the activity of distinct functional subsystems. Moreover, by implementing complex and hierarchically organized control architectures, they allow for an increase in structural and organizational complexity while minimizing fragility. Finally, they endow living systems, from their most basic unicellular instances, with the capability to control their own internal dynamics to adaptively respond to specific features of their interaction with the environment, thus providing the basis for the emergence of minimal forms of cognition. (shrink)

Where is imagination in imaginative resistance? We seek to answer this question by connecting two ongoing lines of inquiry in different subfields of philosophy. In philosophy of mind, philosophers have been trying to understand imaginative attitudes’ place in cognitive architecture. In aesthetics, philosophers have been trying to understand the phenomenon of imaginative resistance. By connecting these two lines of inquiry, we hope to find mutual illumination of an attitude (or cluster of attitudes) and a phenomenon that have vexed (...) philosophers. Our strategy is to reorient the imaginative resistance literature from the perspective of cognitive architecture. Whereas existing taxonomies of positions in the imaginative resistance literature have focused on disagreements over the source and scope of the phenomenon, our taxonomy focuses on the psychological components necessary for explaining imaginative resistance. (shrink)

How did our minds evolve? Can evolutionary considerations illuminate the question of the basic architecture of the human mind? These are two of the main questions addressed in Evolution and the Human Mind by a distinguished interdisciplinary team of philosophers, psychologists, anthropologists and archaeologists. The essays focus especially on issues to do with modularity of mind, the evolution and significance of natural language, and the evolution of our capacity for meta-cognition, together with its implications for consciousness. The editors (...) have provided an introduction that lays out the background to the questions which the essays address, and a consolidated bibliography that will be a valuable reference resource for all those interested in this area. The volume will be of great interest to all researchers and students interested in the evolution and nature of the mind. (shrink)

Diagrams are a form of spatial representation that supports reasoning and problem solving. Even when diagrams are external, not to mention when there are no external representations, problem solving often calls for internal representations, that is, representations in cognition, of diagrammatic elements and internal perceptions on them. General cognitive architectures—Soar and ACT-R, to name the most prominent—do not have representations and operations to support diagrammatic reasoning. In this article, we examine some requirements for such internal representations and processes in (...) cognitive architectures. We discuss the degree to which DRS, our earlier proposal for such an internal representation for diagrams, meets these requirements. In DRS, the diagrams are not raw images, but a composition of objects that can be individuated and thus symbolized, while, unlike traditional symbols, the referent of the symbol is an object that retains its perceptual essence, namely, its spatiality. This duality provides a way to resolve what anti-imagists thought was a contradiction in mental imagery: the compositionality of mental images that seemed to be unique to symbol systems, and their support of a perceptual experience of images and some types of perception on them. We briefly review the use of DRS to augment Soar and ACT-R with a diagrammatic representation component. We identify issues for further research. (shrink)

_Abstract_: Rather than seeking a common architecture for cognitive processing, this paper argues that we should recognize that the brain employs multiple information processing structures. Many of these are manifest in brain areas outside the neocortex such as the hypothalamus, brain stem pattern generators, the basal ganglia, and various nuclei releasing neuromodulators. Rather than employing one mode of information processing, the brain employs multiple modes integrated in a heterarchical network. These in turn affect processing within the neocortex and (...) together with the neocortex regulate vertebrate behavior, including human. Cognitive science can better understand human information processing by attending to the plurality of information-processing architectures employed in the brain. _Keywords_: Basal Ganglia; Cognitive Architectures; Heterarchical Networks; Hypothalamus; Pattern Generators; Neuromodulators _Ripensare l’architettura cognitiva: una rete eterarchica di differenti tipi di elaborazione di informazione_ _Riassunto_: Anziché cercare un’architettura comune ai processi cognitivi, in questo lavoro si sosterrà che dovremmo riconoscere come il cervello impieghi molteplici strutture per processare l’informazione. Molte di loro si trovano nelle aree cerebrali esterne alla neocorteccia, come l’ipotalamo, i generatori di pattern del tronco encefalico, i gangli basali e i vari nuclei che rilasciano i neuromodulatori. Anziché impiegare un’unica modalità per l’elaborazione dell’informazione, il cervello usa molteplici modalità integrate in una rete eterarchica. Queste, a loro volta, influenzano i processi all’interno della neocorteccia e, assieme alla neocorteccia, regolano il comportamento dei vertebrati, compreso quello umano. La scienza cognitiva può meglio comprendere l’elaborazione dell’informazione da parte degli esseri umani concentrandosi sulla pluralità delle architetture impiegate nel cervello per realizzare questa elaborazione. _Parole chiave_: Gangli basali; Architetture cognitive; Reti eterarchiche; Ipotalamo; Generatori di pattern; Neuromodulatori. (shrink)

In this paper, I reinterpret Kant’s Transcendental Analytic as a description of a cognitive architecture. I describe a computer implementation of this architecture, and show how it has been applied to two unsupervised learning tasks. The resulting program is very data efficient, able to learn from a tiny handful of examples. I show how the program achieves data-efficiency: the constraints described in the Analytic of Principles are reinterpreted as strong prior knowledge, constraining the set of possible solutions.

Cognitive architectures - task-general theories of the structure and function of the complete cognitive system - are sometimes argued to be more akin to frameworks or belief systems than scientific theories. The argument stems from the apparent non-falsifiability of existing cognitive architectures. Newell was aware of this criticism and argued that architectures should be viewed not as theories subject to Popperian falsification, but rather as Lakatosian research programs based on cumulative growth. Newell's argument is undermined because he (...) failed to demonstrate that the development of Soar, his own candidate architecture, adhered to Lakatosian principles. This paper presents detailed case studies of the development of two cognitive architectures, Soar and ACT-R, from a Lakatosian perspective. It is demonstrated that both are broadly Lakatosian, but that in both cases there have been theoretical progressions that, according to Lakatosian criteria, are pseudo-scientific. Thus, Newell's defense of Soar as a scientific rather than pseudo-scientific theory is not supported in practice. The ACT series of architectures has fewer pseudo-scientific progressions than Soar, but it too is vulnerable to accusations of pseudo-science. From this analysis, it is argued that successive versions of theories of the human cognitive architecture must explicitly address five questions to maintain scientific credibility. (shrink)

Epistemics as a whole would have a larger scope, encompassing secondary as well as primary individual epistemology and social epistemology in addition. There are a variety of terms of intellectual evaluation, many of interest to epistemology. The ones most commonly used in the discipline are ‘justified’ and ‘rational.’ Another central term of intellectual appraisal, which oddly has received only scant attention in the field, is ‘intelligent.’ Epistemology should be concerned with this range of intellectual assessments. Ethics distinguishes consequentialist and deontological (...) types of theories, and epistemology can utilize the distinction. Which cognitive processes are available, and which are to be approved, are matters that can only be settled with the help of cognitive science. An important distinction drawn in Epistemology and Cognition is the distinction between processes and methods of belief formation. Processes are basic psychological operations, either innate parts of our cognitive architecture or merely the results of maturation as opposed to learning. (shrink)

This paper proposes a brain-inspired cognitive architecture that incorporates approximations to the concepts of consciousness, imagination, and emotion. To emulate the empirically established cognitive efficacy of conscious as opposed to non-conscious information processing in the mammalian brain, the architecture adopts a model of information flow from global workspace theory. Cognitive functions such as anticipation and planning are realised through internal simulation of interaction with the environment. Action selection, in both actual and internally simulated interaction with (...) the environment, is mediated by affect. An implementation of the architecture is described which is based on weightless neurons and is used to control a simulated robot. (shrink)

This chapter contains sections titled: The Systematicity of Inference The Systematicity of Cognitive Representations The Compositionality of Representations Another Systematicity Argument Can Functional Combinatorialism Explain the Systematic Relations in Thought? Conclusion.

Living systems employ several mechanisms and behaviors to achieve robustness and maintain themselves under changing internal and external conditions. Regulation stands out from them as a specific form of higher-order control, exerted over the basic regime responsible for the production and maintenance of the organism, and provides the system with the capacity to act on its own constitutive dynamics. It consists in the capability to selectively shift between different available regimes of self-production and self-maintenance in response to specific signals (...) and perturbations, due to the action of a dedicated subsystem which is operationally distinct from the regulated ones. The role of regulation, however, is not exhausted by its contribution to maintain a living system’s viability. While enhancing robustness, regulatory mechanisms play a fundamental role in the realization of an autonomous biological organization. Specifically, they are at the basis of the remarkable integration of biological systems, insofar as they coordinate and modulate the activity of distinct functional subsystems. Moreover, by implementing complex and hierarchically organized control architectures, they allow for an increase in structural and organizational complexity while minimizing fragility. Finally, they endow living systems, from their most basic unicellular instances, with the capability to control their own internal dynamics to adaptively respond to specific features of their interaction with the environment, thus providing the basis for the emergence of minimal forms of cognition. (shrink)

In this paper we identify and characterize an analysis of two problematic aspects affecting the representational level of cognitive architectures (CAs), namely: the limited size and the homogeneous typology of the encoded and processed knowledge. We argue that such aspects may constitute not only a technological problem that, in our opinion, should be addressed in order to build arti cial agents able to exhibit intelligent behaviours in general scenarios, but also an epistemological one, since they limit the plausibility of (...) the comparison of the CAs' knowledge representation and processing mechanisms with those executed by humans in their everyday activities. In the fi nal part of the paper further directions of research will be explored, trying to address current limitations and future challenges. (shrink)

This paper explores the difference between Connectionist proposals for cognitive a r c h i t e c t u r e a n d t h e s o r t s o f m o d e l s t hat have traditionally been assum e d i n c o g n i t i v e s c i e n c e . W e c l a i m t h a t t (...) h e m a j o r d i s t i n c t i o n i s t h a t , w h i l e b o t h Connectionist and Classical architectures postulate representational mental states, the latter but not the former are committed to a symbol-level of representation, or to a ‘language of thought’: i.e., to representational states that have combinatorial syntactic and semantic structure. Several arguments for combinatorial structure in mental representations are then reviewed. These include arguments based on the ‘systematicity’ of mental representation: i.e., on the fact that cognitive capacities always exhibit certain symmetries, so that the ability to entertain a given thought implies the ability to entertain thoughts with semantically related contents. We claim that such arguments make a powerful case that mind/brain architecture is not Connectionist at the cognitive level. We then consider the possibility that Connectionism may provide an account of the neural (or ‘abstract neurological’) structures in which Classical cognitive architecture is implemented. We survey a n u m b e r o f t h e s t a n d a r d a r g u m e n t s t h a t h a v e b e e n o f f e r e d i n f a v o r o f Connectionism, and conclude that they are coherent only on this interpretation. (shrink)

Barsalou's contribution converges with basic ideas and empirical findings of cognitive linguistics. They posit the same general architecture. The perceptual grounding of conceptual structure is a central tenet of cognitive linguistics. Our capacity to construe the same situation in alternate ways is fundamental to cognitive semantics, and numerous parallels are discernible between conceptual construal and visual perception. Grammar is meaningful, consisting of schematized patterns for the pairing of semantic and phonological structures. The meanings of grammatical (...) elements reside primarily in the construal they impose on conceptual content. This view of linguistic structure appears to be compatible with Barsalou's proposals. (shrink)

As artificial intelligence (AI) thrives and propagates through modern life, a key question to ask is how to include humans in future AI? Despite human involvement at every stage of the production process from conception and design through to implementation, modern AI is still often criticized for its “black box” characteristics. Sometimes, we do not know what really goes on inside or how and why certain conclusions are met. Future AI will face many dilemmas and ethical issues unforeseen by their (...) creators beyond those commonly discussed (e.g., trolley problems and variants of it) and to which solutions cannot be hard-coded and are often still up for debate. Given the sensitivity of such social and ethical dilemmas and the implications of these for human society at large, when and if our AI make the “wrong” choice we need to understand how they got there in order to make corrections and prevent recurrences. This is particularly true in situations where human livelihoods are at stake (e.g., health, well-being, finance, law) or when major individual or household decisions are taken. Doing so requires opening up the “black box” of AI; especially as they act, interact, and adapt in a human world and how they interact with other AI in this world. In this article, we argue for the application of cognitive architectures for ethical AI. In particular, for their potential contributions to AI transparency, explainability, and accountability. We need to understand how our AI get to the solutions they do, and we should seek to do this on a deeper level in terms of the machine-equivalents of motivations, attitudes, values, and so on. The path to future AI is long and winding but it could arrive faster than we think. In order to harness the positive potential outcomes of AI for humans and society (and avoid the negatives), we need to understand AI more fully in the first place and we expect this will simultaneously contribute towards greater understanding of their human counterparts also. (shrink)

Human vision supports social perception by efficiently detecting agents and extracting rich information about their actions, goals, and intentions. Here, we explore the cognitive architecture of perceived animacy by constructing Bayesian models that integrate domain‐specific hypotheses of social agency with domain‐general cognitive constraints on sensory, memory, and attentional processing. Our model posits that perceived animacy combines a bottom–up, feature‐based, parallel search for goal‐directed movements with a top–down selection process for intent inference. The interaction of these architecturally distinct (...) processes makes perceived animacy fast, flexible, and yet cognitively efficient. In the context of chasing, in which a predator (the “wolf”) pursues a prey (the “sheep”), our model addresses the computational challenge of identifying target agents among varying numbers of distractor objects, despite a quadratic increase in the number of possible interactions as more objects appear in a scene. By comparing modeling results with human psychophysics in several studies, we show that the effectiveness and efficiency of human perceived animacy can be explained by a Bayesian ideal observer model with realistic cognitive constraints. These results provide an understanding of perceived animacy at the algorithmic level—how it is achieved by cognitive mechanisms such as attention and working memory, and how it can be integrated with higher‐level reasoning about social agency. (shrink)

The dynamic approach to understanding of the human consciousness, its cognitive activities and cognitive architecture is one of the most promising approaches in the modern epistemology and cognitive science. The conception of embodied mind is under discussion in the light of nonlinear dynamics and of the idea co-evolution of complex systems developed by the Moscow scientific school. The cognitive architecture of the embodied mind is rather complex: data from senses and products of rational thinking, (...) the verbal and the pictorial, logic and intuition, the analytical and synthetic abilities of perception and of thinking, the local and the global, the analogue and the digital, the archaic and the post-modern are intertwined in it. In the process of cognition, co-evolution of embodied mind as an autopoietic system and its surroundings takes place. The perceptual and mental processes are bound up with the structure of human body. Nonlinear and circular connecting links between the subject of cognition and the world constructed by him can be metaphorically called a nonlinear cobweb of cognition. Cognition is an autopoietic activity because it is directed to the search of elements that are missed; it serves to completing integral structures. According to the theory of blow-up regimes in complex systems elaborated by Sergey P.Kudyumov and his followers, the idea of co-evolution is connected with the concept of tempoworlds. To co-evolve means to start to develop in one and the same tempoworld and to use the possibility – in case of a proper intergation into a whole structure – to accelerate the tempo of evolution. The cognitive activities of the human being can be considered as a movement (active walk) in landscapes of co-evolution when he cognizes and changes environment and is changed himself by the very activities. The similar conclusion can be drawn from Francisco Varela’s conception of enactive cognition. (shrink)

In cognitive science, the concept of dissociation has been central to the functional individuation and decomposition of cognitive systems. Setting aside debates about the legitimacy of inferring the existence of dissociable systems from ‘behavioural’ dissociation data, the main idea behind the dissociation approach is that two cognitive systems are dissociable, and thus viewed as distinct, if each can be damaged, or impaired, without affecting the other system’s functions. In this article, I propose a notion of functional independence (...) that does not require dissociability, and describe an approach to the functional decomposition and modelling of cognitive systems that complements the dissociation approach. I show that highly integrated cognitive and neurocognitive systems can be decomposed into non-dissociable but functionally independent components, and argue that this approach can provide a general account of cognitive specialization in terms of a stable structure–function relationship. 1 Introduction2 Functional Independence without Dissociability3 FI Systems and Cognitive Architecture4 FI Systems and Cognitive Specialization. (shrink)

The central contention of The Implicit Mind is that understanding the two faces of spontaneity-its virtues and vices-requires understanding the "implicit mind." In turn, Michael Brownstein maintains that understanding the implicit mind requires the consideration of three sets of questions. First, what are implicit mental states? What kind of cognitive structure do they have? Second, how should we relate to our implicit attitudes? Are we responsible for them? Third, how can we improve the ethics of our implicit minds?

During the last decades, many cognitive architectures (CAs) have been realized adopting different assumptions about the organization and the representation of their knowledge level. Some of them (e.g. SOAR [35]) adopt a classical symbolic approach, some (e.g. LEABRA[ 48]) are based on a purely connectionist model, while others (e.g. CLARION [59]) adopt a hybrid approach combining connectionist and symbolic representational levels. Additionally, some attempts (e.g. biSOAR) trying to extend the representational capacities of CAs by integrating diagrammatical representations and reasoning (...) are also available [34]. In this paper we propose a reflection on the role that Conceptual Spaces, a framework developed by Peter G¨ardenfors [24] more than fifteen years ago, can play in the current development of the Knowledge Level in Cognitive Systems and Architectures. In particular, we claim that Conceptual Spaces offer a lingua franca that allows to unify and generalize many aspects of the symbolic, sub-symbolic and diagrammatic approaches (by overcoming some of their typical problems) and to integrate them on a common ground. In doing so we extend and detail some of the arguments explored by G¨ardenfors [23] for defending the need of a conceptual, intermediate, representation level between the symbolic and the sub-symbolic one. In particular we focus on the advantages offered by Conceptual Spaces (w.r.t. symbolic and sub-symbolic approaches) in dealing with the problem of compositionality of representations based on typicality traits. Additionally, we argue that Conceptual Spaces could offer a unifying framework for interpreting many kinds of diagrammatic and analogical representations. As a consequence, their adoption could also favor the integration of diagrammatical representation and reasoning in CAs. (shrink)

"Cognitive Architecture" asks how evolving modalities--from bio-politics to "noo-politics"--can be mapped upon the city under contemporary conditions of urbanization and globalization. Noo-politics, most broadly understood as the power exerted over the life of the mind, reconfigures perception, memory and attention, and also implicates potential ways and means by which neurobiological architecture is undergoing reconfiguration. This volume, motivated by theories such as 'cognitive capitalism' and concepts such as 'neural plasticity, ' shows how architecture and urban processes (...) and products commingle to form complex systems that produce novel forms of networks that empower the imagination and constitute the cultural landscape. This volume rethinks the relations between form and forms of communication, calling for a new logic of representation; it examines the manner in which information, with its non-hierarchical and distributed format is contributing both to the sculpting of brain and production of mind. "Cognitive Architecture" brings together renowned specialists in the areas of political and aesthetic philosophy, neuroscience, socio-cultural and architecture theory, visual and spatial theorists and practitioners. (shrink)

First published in 1998. Routledge is an imprint of Taylor & Francis, an informa company.

Cognitive architectures, like programming languages, make commitments only at the implementation level and have limited explanatory power. Their universality implies that it is hard, if not impossible, to justify them in detail from finite quantities of data. It is more fruitful to focus on particular tasks such as language understanding and propose testable theories at the computational and algorithmic levels.

Two long-standing arguments in cognitive science invoke the assumption that holistic inference is computationally infeasible. The first is Fodor’s skeptical argument toward computational modeling of ordinary inductive reasoning. The second advocates modular computational mechanisms of the kind posited by Cosmides, Tooby and Sperber. Based on advances in machine learning related to Bayes nets, as well as investigations into the structure of scientific and ordinary information, I maintain neither argument establishes its architectural conclusion. Similar considerations also undermine Fodor’s decades-long diagnosis (...) of artificial intelligence research as confounded by an inability to circumscribe the amount of information relevant to inferential processes. This diagnosis is particularly inapposite with respect to Bayes nets, since one of their strengths as machine learning systems has been their capacity to reason probabilistically about large data sets whose size overwhelms the capacities of individual human reasoners. A general moral follows from these criticisms: Insights into artificial and human cognitive systems are likely to be cultivated by focusing greater attention on the structure and density of connections among items of information that are available to them. (shrink)

This volume rethinks the relations between form and forms of communication, calling for a new logic of representation; it examines the manner in which ...

As we know, a cognitive architecture is a domain-generic computational cognitive model that may be used for a broad analysis of cognition and behavior. Cognitive architectures embody theories of cognition in computer algorithms and programs. Social simulation with multi-agent systems can benefit from incorporating cognitive architectures, as they provide a realistic basis for modeling individual agents (as argued in Sun 2001). In this survey, an example cognitive architecture will be given, and its application (...) to social simulation will be sketched. (shrink)