Marr's seminal work laid out a program of research by specifying key questions for cognitive science at different levels of analysis. Because dynamic systems theory focuses on time and interdependence of components, DST research programs come to very different conclusions regarding the nature of cognitive change. We review a specific DST approach to cognitive-level processes: dynamic field theory. We review research applying DFT to several cognitive-level processes: object permanence, naming hierarchical categories, and inferring intent, that (...) demonstrate the difference in understanding of behavior and cognition that results from a DST perspective. These point to a central challenge for cognitive science research as defined by Marr—emergence. We argue that appreciating emergence raises questions about the utility of computational-level analyses and opens the door to insights concerning the origin of novel forms of behavior and thought. We contend this is one of the most fundamental questions about cognition and behavior. (shrink)

This paper argues that the Extended Synthesis, ecological information, and biosemiotics are complementary approaches whose engagement will help us explain the organism-environment interaction at the cognitive level. The Extended Synthesis, through niche construction theory, can explain the organism-environment interaction at an evolutionary level because niche construction is a process guided by information. We believe that the best account that defines information at this level is the one offered by biosemiotics and, within all kinds of biosemiotic information available, we believe (...) that ecological information is the best candidate for making sense of the organism-environment relation at the cognitive level. This entanglement of biosemiotics, ecological information and the Extended Synthesis is promising for understanding the multidimensional character of the organism-environment reciprocity as well as the relation between evolution, cognition, and meaning. (shrink)

Before a general cognitive model for recurrent complex visual hallucinations (RCVH) is accepted, there must be more research into the neuropsychological and cognitive characteristics of the various disorders in which they occur. Currently available data are insufficient to distinguish whether the similar phenomenology of RCVH across different disorders is in fact produced by a single or by multiple cognitive mechanisms.

This paper connects information with computation and cognition via concept of agents that appear at variety of levels of organization of physical/chemical/cognitive systems – from elementary particles to atoms, molecules, life-like chemical systems, to cognitive systems starting with living cells, up to organisms and ecologies. In order to obtain this generalized framework, concepts of information, computation and cognition are generalized. In this framework, nature can be seen as informational structure with computational dynamics, where an (info-computational) agent is (...) needed for the potential information of the world to actualize. Starting from the definition of information as the difference in one physical system that makes a difference in another physical system – which combines Bateson and Hewitt’s definitions, the argument is advanced for natural computation as a computational model of the dynamics of the physical world, where information processing is constantly going on, on a variety of levels of organization. This setting helps us to elucidate the relationships between computation, information, agency and cognition, within the common conceptual framework, with special relevance for biology and robotics. (shrink)

David Marr provided an influential account of levels of description in classical cognitive science. In this paper we contrast Marr'ent with some alternatives that are suggested by the recent emergence of connectionism. Marr's account is interesting and important both because of the levels of description it distinguishes, and because of the way his presentation reflects some of the most basic, foundational, assumptions of classical AI-style cognitive science. Thus, by focusing on levels of description, one can (...) sharpen foundational differences between classicism and potential non-classical conceptions of mentality that might emerge under the rubric of connectionism. (shrink)

There has been a recent surge in interest in two questions concerning the nature of perceptual experience; viz. the question of whether perceptual experience is sometimes cognitively penetrated and that of whether high-level properties are presented in perceptual experience. Only rarely have thinkers been concerned with the question of whether the two phenomena are interestingly related. Here we argue that the two phenomena are not related in any interesting way. We argue further that this lack of an interesting connection between (...) the two phenomena has potentially devastating consequences for naïve realism. Finally, we consider the possibility of a disunified view of experience that takes perceptual experience to be a matter of both being directly perceptually related to mind-independent objects and property instances as well as consciously representing these entities. (shrink)

The notion of levels has been widely used in discussions of cognitive science, especially in discussions of the relation of connectionism to symbolic modeling of cognition. I argue that many of the notions of levels employed are problematic for this purpose, and develop an alternative notion grounded in the framework of mechanistic explanation. By considering the source of the analogies underlying both symbolic modeling and connectionist modeling, I argue that neither is likely to provide an adequate analysis (...) of processes at the level at which cognitive theories attempt to function: One is drawn from too low a level, the other from too high a level. If there is a distinctly cognitive level, then we still need to determine what are the basic organizational principles at that level. (shrink)

Some controversies in cognitive science, such as arguments about whether classical or distributed connectionist architectures best model the human cognitive system, reenact long‐standing debates in the philosophy of science. For millennia, philosophers have pondered whether mentality can submit to scientific explanation generally and to physical explanation particularly. Recently, positive answers have gained popularity. The question remains, though, as to the analytical level at which mentality is best explained. Is there a level of analysis that is peculiarly appropriate to (...) the explanation of either consciousness or mental contents? Are human consciousness, cognition, and conduct best understood in terms of talk about neurons and networks or schemas and scripts or intentions and inferences? If our best accounts make no appeal to our hopes or beliefs or desires, how do we square those views with our conception of ourselves as rational beings? Moreover, can models of physical processes explain our mental lives? Does mentality require a special level of rational or cognitive explanation, or is it best understood in terms of overall brain functioning or neuronal or molecular or even quantum activities – or any of a dozen levels of physical explanation in between? Also, regardless of how they compare with explanations cast at physical levels, what is the status of psychological explanations that appeal fundamentally to mental contents? (shrink)

David Sloan Wilson has recently revived the idea of a group mind as an application of group selectionist thinking to cognition. Central to my discussion of this idea is the distinction between the claim that groups have a psychology and what I call the social manifestation thesis-a thesis about the psychology of individuals. Contemporary work on this topic has confused these two theses. My discussion also points to research questions and issues that Wilson's work raises, as well as their connection (...) to externalist conceptions of the mind familiar since the work of Putnam and Burge. (shrink)

In Philosophy of Psychedelics, Letheby provides a convincing basis for the idea that psychedelics primarily derive their therapeutic potential through mediating favourable changes to self-related belief systems. In this commentary, we take a closer look at the role that contextual factors play in Letheby’s two-factor account of psychedelic therapy. While Letheby acknowledges that psychedelic effects are highly context-dependent, the exact role that context plays in self-modelling during the acute experience is not entirely clear. We argue that context plays an essential (...) role in shaping the ‘discovery’ of alternate self-conceptions during the acute experience. Specifically, users are more likely to experience alterations in self-conception that are consistent with context-dependent features, such as one’s prior mindset and aspects of the external environment. This is consistent with a REBUS model of psychedelic effects, where a corollary effect of relaxing high-level prior beliefs is that the system becomes increasingly sensitised to bottom-up information from lower-level intrinsic sources and the sensory periphery. Furthermore, it may explain why a positive well-intentioned state of mind and a supportive therapeutic environment are more likely to result in positive acute experiences and long-term improvements in mental wellbeing. We see this position as being largely compatible with Letheby’s proposal, but may shift some aspects of its emphasis and framing. In particular, it may conflict with Letheby’s notion that psychedelics lead to a ‘level cognitive playing field’, where self-related hypotheses are thought to be assigned more or less equal probability. (shrink)

The article first addresses the importance of cognitive modeling, in terms of its value to cognitive science (as well as other social and behavioral sciences). In particular, it emphasizes the use of cognitive architectures in this undertaking. Based on this approach, the article addresses, in detail, the idea of a multi-level approach that ranges from social to neural levels. In physical sciences, a rigorous set of theories is a hierarchy of descriptions/explanations, in which causal relationships among (...) entities at a high level can be reduced to causal relationships among simpler entities at a more detailed level. We argue that a similar hierarchy makes possible an equally productive approach toward cognitive modeling. The levels of models that we conceive in relation to cognition include, at the highest level, sociological/anthropological models of collective human behavior, behavioral models of individual performance, cognitive models involving detailed mechanisms, representations, and processes, as well as biological/physiological models of neural circuits, brain regions, and other detailed biological processes. (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)

Talk of levels is everywhere in cognitive science. Whether it is in terms of adjudicating longstanding debates or motivating foundational concepts, one cannot go far without hearing about the need to talk at different ‘levels’. Yet in spite of its widespread application and use, the concept of levels has received little sustained attention within cognitive science. This paper provides an analysis of the various ways the notion of levels has been deployed within cognitive (...) science. The paper begins by introducing and motivating discussion via four representative accounts of levels. It then turns to outlining and relating the four accounts using two dimensions of comparison. The result is the creation of a conceptual framework that maps the logical space of levels talk, which offers an important step toward making sense of levels talk within cognitive science. (shrink)

Marr's levels of analysis—computational, algorithmic, and implementation—have served cognitive science well over the last 30 years. But the recent increase in the popularity of the computational level raises a new challenge: How do we begin to relate models at different levels of analysis? We propose that it is possible to define levels of analysis that lie between the computational and the algorithmic, providing a way to build a bridge between computational- and algorithmic-level models. The key idea (...) is to push the notion of rationality, often used in defining computational-level models, deeper toward the algorithmic level. We offer a simple recipe for reverse-engineering the mind's cognitive strategies by deriving optimal algorithms for a series of increasingly more realistic abstract computational architectures, which we call “resource-rational analysis.”. (shrink)

Distributed Cognition and Integrational Linguistics have much in common. Both approaches see communicative activity and intelligent behaviour in general as strongly con- text-dependent and action-oriented, and brains as permeated by history. But there is some ten- sion between the two frameworks on three important issues. The majority of theorists of distributed cognition want to maintain some notions of mental representation and computa- tion, and to seek generalizations and patterns in the various ways in which creatures like us couple with technologies, (...) media, and other agents; many also want to offer explanations at subpersonal levels which may undercut the autonomy of personal-level accounts. In contrast, dominant views in integrational linguistics reject all invocation of representation, resist the explanatory search for similarity across contexts and moments, and see linguistics as a lay dis- cipline which should not offer explanations in terms alien to ordinary agents. On each of these issues, I argue that integrationists could move closer to the distributed cognition frame- work without losing the most important aspects of their view: integrationist criticisms of mainstream or classical theories can be respected while alliances with revised cognitivist views about representation, context, and explanation are developed. Ó 2004 Elsevier Ltd. All rights reserved. (shrink)

We consider approaches to explanation within the cognitive sciences that begin with Marr's computational level or Marr's implementational level and argue that each is subject to fundamental limitations which impair their ability to provide adequate explanations of cognitive phenomena. For this reason, it is argued, explanation cannot proceed at either level without tight coupling to the algorithmic and representation level. Even at this level, however, we argue that additional constraints relating to the decomposition of the cognitive system (...) into a set of interacting subfunctions are required. Integrated cognitive architectures that permit abstract specification of the functions of components and that make contact with the neural level provide a powerful bridge for linking the algorithmic and representational level to both the computational level and the implementational level. (shrink)

Mental representation has long been central to standard accounts of action and cognition generally, and in the context of sport. We argue for an enactive and embodied account that rejects the idea that representation is necessary for cognition, and posit instead that cognition arises, or is enacted, in certain types of interactions between organisms and their environment. More specifically, we argue that enactive theories explain some kinds of high-level cognition, those that underlie some of the best performances in sport and (...) similar practices (dance, martial arts), better than representational accounts. Flow and mushin (mindfully fluid awareness) are explained enactively to this end. This results in a mutually beneficial analysis where enactivism offers theoretical and practical advantages as an explanation of high performance in sports, while the latter validates enactivism. (shrink)

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)

"Each animal in its own psychological setting . . / 1 Gerard Piel Scientific American, New York TC Schneirla was more interested in questions than in ...

Imitation in robotics is seen as a powerful means to reduce the complexity of robot programming. It allows users to instruct robots by simply showing them how to execute a given task. Through imitation robots can learn from their environment and adapt to it just as human newborns do. Despite different facets of imitative behaviours observed in humans and higher primates, imitation in robotics has usually been implemented as a process of copying demonstrated actions onto the movement apparatus of the (...) robot. While the results being reached are impressive, we believe that a shift towards a higher expression of imitation, namely the comprehension of human actions and inference of its intentions, is needed. In order to be useful as human companions, robots must act for a purpose by achieving goals and fulfilling human expectations. In this paper we present ConSCIS, an architecture for goal-level imitation in robotics where the focus is put on final effects of actions on objects. The architecture tightly links low-level data with high-level knowledge, and integrates, in a unified framework, several aspects of imitation, such as perception, learning, knowledge representation, action generation and robot control. Some preliminary experimental results with an anthropomorphic arm/hand robotic system are shown. (shrink)

Imitation in robotics is seen as a powerful means to reduce the complexity of robot programming. It allows users to instruct robots by simply showing them how to execute a given task. Through imitation robots can learn from their environment and adapt to it just as human newborns do. Despite different facets of imitative behaviours observed in humans and higher primates, imitation in robotics has usually been implemented as a process of copying demonstrated actions onto the movement apparatus of the (...) robot. While the results being reached are impressive, we believe that a shift towards a higher expression of imitation, namely the comprehension of human actions and inference of its intentions, is needed. In order to be useful as human companions, robots must act for a purpose by achieving goals and fulfilling human expectations. In this paper we present ConSCIS, an architecture for goal-level imitation in robotics where the focus is put on final effects of actions on objects. The architecture tightly links low-level data with high-level knowledge, and integrates, in a unified framework, several aspects of imitation, such as perception, learning, knowledge representation, action generation and robot control. Some preliminary experimental results with an anthropomorphic arm/hand robotic system are shown. (shrink)

Over the past century or more, cognitive neuropsychologists have discussed many of the issues raised in this volume. On the basis of this literature, we argue that autism is not a single homogeneous condition, and so can have no single cause. Instead, each of its symptoms has a cause, and the proper study of autism is the separate study of each of these symptoms and its cause. We also offer evidence to support the radical view advanced by Stoljar and (...) Gold in this volume, namely, that in explaining such syndromes the cognitive level of explanation has priority over the neuroscientific. (shrink)

ABSTRACT Dance requires optimal range-of-motion and cognitive abilities. Mental imagery is a recommended, yet under-researched, training method for enhancing both of these. This study investigated the effect of Dynamic Neuro-Cognitive Imagery (DNI™) training on developpé performance (measured by gesturing ankle height and self-reported observations) and kinematics (measured by hip and pelvic range-of-motion), as well as on dance imagery abilities. Thirty-four university-level dance students (M age = 19.70 + 1.57) were measured performing three developpé tasks (i.e., 4 repetitions, 8 (...) consecutive seconds hold, and single repetition) at three time-points (2 x pre-, 1 x post-intervention). Data were collected using three-dimensional motion capture, mental imagery questionnaires, and subjective reports. Following the DNI™ intervention, significant increases (p <.01) were detected in gesturing ankle height, as well as in hip flexion and abduction range-of-motion, without significant changes in pelvic alignment. These gains were accompanied by self-reported decrease (p <.05) in level of difficulty experienced and significant improvements in kinesthetic (p <.05) and dance (p <.01) imagery abilities. This study provides evidence for the motor and non-motor benefits of DNI™ training in university-level dance students. (shrink)

This monograph provides a new account of justified inference as a cognitive process. In contrast to the prevailing tradition in epistemology, the focus is on low-level inferences, i.e., those inferences that we are usually not consciously aware of and that we share with the cat nearby which infers that the bird which she sees picking grains from the dirt, is able to fly. Presumably, such inferences are not generated by explicit logical reasoning, but logical methods can be used to (...) describe and analyze such inferences. Part 1 gives a purely system-theoretic explication of belief and inference. Part 2 adds a reliabilist theory of justification for inference, with a qualitative notion of reliability being employed. Part 3 recalls and extends various systems of deductive and nonmonotonic logic and thereby explains the semantics of absolute and high reliability. In Part 4 it is proven that qualitative neural networks are able to draw justified deductive and nonmonotonic inferences on the basis of distributed representations. This is derived from a soundness/completeness theorem with regard to cognitive semantics of nonmonotonic reasoning. The appendix extends the theory both logically and ontologically, and relates it to A. Goldman's reliability account of justified belief. This text will be of interest to epistemologists and logicians, to all computer scientists who work on nonmonotonic reasoning and neural networks, and to cognitive scientists. (shrink)

This paper focuses on the cognitive/computational and evolutionary levels. It describes three proposals to make cognition computationally tractable, namely: Resource Rationality, the Adaptive Toolbox and Massive Modularity. While each of these proposals appeals to evolutionary considerations to dissolve the intractability of cognition, Rich, Blokpoel, de Haan, and van Rooij argue that, in each case, the intractability challenge is not resolved, but just relocated to the level of evolution.

David Marr provided an influential account of levels of description in classical cognitive science. In this paper we contrast Marr'ent with some alternatives that are suggested by the recent emergence of connectionism. Marr's account is interesting and important both because of the levels of description it distinguishes, and because of the way his presentation reflects some of the most basic, foundational, assumptions of classical AI-style cognitive science . Thus, by focusing on levels of description, one (...) can sharpen foundational differences between classicism and potential non-classical conceptions of mentality that might emerge under the rubric of connectionism. (shrink)

Cognitive science began as a multidisciplinary endeavor to understand how the mind works. Since the beginning, cognitive scientists have been asking questions about the right methodologies and levels of explanation to pursue this goal, and make cognitive science a coherent science of the mind. Key questions include: Is there a privileged level of explanation in cognitive science? How do different levels of explanation fit together, or relate to one another? How should explanations at one (...) level inform or constrain explanations at some other level? Can the different approaches to the mind, brain, and culture be unified? The aim of this issue of topiCS is to provide a platform for discussing different answers to such questions and to facilitate a better understanding between the different strands of thinking about the right levels of explanation in cognitive science. (shrink)

Drawing heavily on recent empirical research to update R.M. Hare's two-level utilitarianism and expand Hare's treatment of "intuitive level rules," Gary Varner considers in detail the theory's application to animals while arguing that Hare should have recognized a hierarchy of persons, near-persons, & the merely sentient.

This paper focuses on the cognitive/computational and evolutionary levels. It describes three proposals to make cognition computationally tractable, namely: Resource Rationality, the Adaptive Toolbox and Massive Modularity. While each of these proposals appeals to evolutionary considerations to dissolve the intractability of cognition, Rich, Blokpoel, de Haan, and van Rooij argue that, in each case, the intractability challenge is not resolved, but just relocated to the level of evolution.

Over the past century or more, cognitive neuropsychologists have discussed many of the issues raised in this volume. On the basis of this literature, we argue that autism is not a single homogeneous condition, and so can have no single cause. Instead, each of its symptoms has a cause, and the proper study of autism is the separate study of each of these symptoms and its cause. We also offer evidence to support the radical view advanced by Stoljar and (...) Gold in this volume, namely, that in explaining such syndromes the cognitive level of explanation has priority over the neuroscientific. (shrink)

Philosophers and psychologists alike have argued recently that relatively abstract beliefs or cognitive categories like those regarding race can influence the perceptual experience of relatively low-level visual features like color or lightness. Some of the proposed best empirical evidence for this claim comes from a series of experiments in which White faces were consistently judged as lighter than equiluminant Black faces, even for racially ambiguous faces that were labeled ‘White’ as opposed to ‘Black’ (Levin and Banaji 2006). The latter (...) result is considered especially indicative of cognitive penetration, based on the reasoning that the relevant distortions were a function of lexical labeling, and hence the effect must have been mediated by categorization at the cognitive level. I argue that this reasoning is flawed, and that the assumptions on which it relies are questionable on both empirical and theoretical grounds. I propose an alternative, low-level explanation of the phenomena, which I argue is empirically more plausible and abductively preferable to the cognitive-penetration account. The upshot is that cognitively impenetrable perceptual systems may be psychologically more plastic and hence philosophically more significant than is nowadays commonly assumed. (shrink)

Research on unethical pro-organizational behavior has predominantly focused on its antecedents, while overlooking how engaging in such behavior might affect employees’ psychological experience and their downstream work behaviors. Integrating cognitive dissonance theory with the moral identity literature, we argue that engaging in UPB restricts moral identity internalization as a result of attempts to alleviate the cognitive dissonance about moral self-regard, which in turn translates into decreased organizational citizenship behavior and increased counterproductive workplace behavior. Moreover, employees’ construal level weakens (...) these indirect effects by alleviating the negative effect of engaging in UPB on moral identity internalization. The results from one experimental study and one multi-wave, multisource field study provide support for these predictions. Our research extends knowledge on the negative consequences of UPB for actors and organizations. (shrink)

This informative and conceptually stimulating target article is very useful. I merely query whether the term “illusory contours” is appropriate for gap filling; “illusory surfaces” seems better – and “fictional surfaces” better still. These seem to be rule based rather than knowledge based, suggesting indeed the importance of distinguishing rules (analogous to syntax in language) from knowledge (equivalent to semantics) for classifying perceptual phenomena.

The aim of cognitive diagnosis is to classify respondents' mastery status of latent attributes from their responses on multiple items. Since respondents may answer some but not all items, item-level missing data often occur. Even if the primary interest is to provide diagnostic classification of respondents, misspecification of missing data mechanism may lead to biased conclusions. This paper proposes a joint cognitive diagnosis modeling of item responses and item-level missing data mechanism. A Bayesian Markov chain Monte Carlo method (...) is developed for model parameter estimation. Our simulation studies examine the parameter recovery under different missing data mechanisms. The parameters could be recovered well with correct use of missing data mechanism for model fit, and missing that is not at random is less sensitive to incorrect use. The Program for International Student Assessment 2015 computer-based mathematics data are applied to demonstrate the practical value of the proposed method. (shrink)

This paper shows that recent arguments from group problem solving and task performance to emergent group level cognition that rest on the social parity and related principles are invalid or question begging. The paper shows that standard attributions of problem solving or task performance to groups require only multiple agents of the outcome, not a group agent over and above its members, whether or not any individual member of the group could have accomplished the task independently.

A 3rd person Knowledge Level analysis of cognitive architectures -/- Abstract I provide a knowledge level analysis of the main representational and reasoning problems affecting the cognitive architectures for what concerns this issue. In providing this analysis I will show, by considering some of the main cognitive architectures currently available (e.g. SOAR, ACT-R, CLARION), how one of the main problems of such architectures is represented by the fact that their knowledge representation and processing mechanisms are not sufficiently (...) constrained with “structural insights” (Lieto 2021) coming from cognitive science for dealing with commonsense knowledge and reasoning (Lebiere, Oltramari, 2018). As a possible way out to such knowledge processing issues, I present the main assumptions that have led to the development of the Dual PECCS categorization system (Lieto, Radicioni, Rho 2017) and discuss some of the lessons learned and their possible implications in the design of the knowledge modules and knowledge-processing mechanisms of integrated cognitive architectures. (shrink)

In approaching the question of whether groups of people can have cognitive capacities that are fundamentally different than the cognitive capacities of the individuals within the group, we lay out a Multiple, Interactive Levels of Cognitive Systems (MILCS) framework. The goal of MILCS is to explain the kinds of cognitive processes typically studied by cognitive scientists, such as perception, attention, memory, categorization, decision making, problem solving, and judgment. Rather than focusing on high-level constructs such (...) as modules in an information processing flow diagram or internal representations, MILCS focuses on mechanisms that allow systems to engage in flexible, adaptive behavior. Examples of these mechanisms are network structure-process pairs that: combine data from perception with top-down theories, achieve consistency and consensus through information exchange, selectively attend to information globally assessed as relevant, and develop specialized units from originally homogeneous networks through competition among the units. Two such systems are considered in some detail -- lateral inhibition within a network for selecting from a candidate set the option that is most attractive, and a diffusion process for accumulating evidence to reach a generally rapid and accurate decision. These system descriptions are aptly applied at multiple levels, including within and across people. These systems provide accounts that unify cognitive processes across multiple levels, can be expressed in a common vocabulary provided by network science, are inductively powerful yet appropriately constrained, and are applicable to a large number of superficially diverse cognitive systems. Given that people are typically highly motivated to participate in strong groups, cognitively resourceful people will tend to form groups that effectively employ cognitive systems at higher levels than the individuals. The impressive cognitive capacities of individual people do not eliminate the need to talk about group cognition. Instead, smart people generally form smart groups. (shrink)

Thirty years after the publication of Marr's seminal book Vision the papers in this topic consider the contemporary status of his influential conception of three distinct levels of analysis for information-processing systems, and in particular the role of the algorithmic and representational level with its cognitive-level concepts. This level has been downplayed or eliminated both by reductionist neuroscience approaches from below that seek to account for behavior from the implementation level and by Bayesian approaches from above that seek (...) to account for behavior in purely computational-level terms. (shrink)

Research in cognitive science has often assumed the existence of a privileged level that unifies theoretical explanations arising from different disciplines. Philosophical accounts differ about the locus of those intertheory relations. In this paper, four different views are analyzed: classical, connectionist, pragmatist, and reductionist, as exemplified in the works of von Eckardt, Horgan and Tienson, Hardcastle, and Bickle, respectively. Their divergences are characterized in terms of the possibility of such a privileged level. The classical view favors a privileged computational (...) level. The connectionist revision tries to draw biological intuitions into computational models to provide a link between neurons and computations. The pragmatist approach rejects the idea of a privileged level and offers a more eclectic view of cognitive theory building. The reductionist account pursues theoretical unification by means of the reduction of higher level theories to basic level ones. /// La investigatión en ciencia cognitiva suele asumir la existencia de un nivel privilegiado que unifica las explicaciones teóricas provenientes de distintas disciplinas. Las interpretaciones filósoficas difieren respecto al locus de tales relaciones interteóricas. En este artículo se analizan cuatro concepciones: clásica, conexionista, pragmática y reduccionista, ejemplificadas respectivamente en las obras de von Eckardt, Horgan y Tienson, Hardcastle y Bickle. Sus divergencias se caracterizan en términos de la posible existencia del nivel privilegiado. El enfoque clásico propugna un nivel privilegiado computacional. La revisión conexionista importa intuiciones de la biología a los modelos computacionales, con la intentión de vincular lo neuronal con lo computacional. El enfoque pragmático rechaza la idea de un nivel privilegiado y ofrece una visión más ecléctica de la teorización cognitiva. La conceptión reduccionista promueve la unificatión teórica mediante la reductión de teorías de alto nivel a teorías de nivel básico. (shrink)

Philosophers of mind commonly draw a distinction between the personal level – the distinctive realm of conscious experience and reasoned deliberation – and the subpersonal level, the domain of mindless mechanism and brute cause and effect. Moreover, they tend to view cognitive science through the lens of this distinction. Facts about the personal level are given a priori, by introspection, or by common sense; the job of cognitive science is merely to investigate the mechanistic basis of these facts. (...) I argue that this view misrepresents the structure of cognitive-scientific enquiry. Taken at face value, cognitive science makes no commitment to the existence of a distinctive level at which persons or selves appear. Thus, in the age of cognitive science, we should not expect to find the self in an ontologically distinct realm. Instead, we should expect to locate it in cognitive-scientific models themselves. In closing, I indicate likely results of this approach. (shrink)