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Switch to: References
Citations of:
A non-representational approach to imagined action
Cognitive Science 26 (3):345-375 (2002)
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According to a standard representationalist view cognitive capacities depend on internal content-carrying states. Recent alternatives to this view have been met with the reaction that they have, at best, limited scope, because a large range of cognitive phenomena—those involving absent and abstract features—require representational explanations. Here we challenge the idea that the consideration of cognition regarding the absent and the abstract can move the debate about representationalism along. Whether or not cognition involving the absent and the abstract requires the positing (...) |
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Imagination is often considered the pinnacle of representational cognition. Looking at the concrete details of imagining in context, this paper aims to contribute to the emerging literature that is challenging this representational view by offering a relational and radically situated alternative. On the basis of observing architects in the process of making an architectural art installation, we show how to consider imagination not as de-contextualized achievement by an individual but as an opening up to larger-scale “affordances,” i.e. the unfolding possibilities (...) |
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Despite the gaining popularity of non-representationalist approaches to cognition, it is still a widespread assumption in contemporary cognitive science that the explanatory reach of representation-eschewing approaches is substantially limited. Nowadays, many working in the field accept that we do not need to invoke internal representations for the explanation of online forms of cognition. However, when it comes to explaining higher, offline forms of cognition, it is widely believed that we must fall back on internal-representation-invoking theories. In this paper, I want (...) |
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In recent years the cognitive science community has witnessed the rise of a new, dynamical approach to cognition. This approach entails a framework in which cognition and behavior are taken to result from complex dynamical interactions between brain, body, and environment. The advent of the dynamical approach is grounded in a dissatisfaction with the classical computational view of cognition. A particularly strong claim has been that cognitive systems do not rely on internal representations and computations. Focusing on this claim, we (...) |
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Imagination is often considered the pinnacle of representational cognition. Looking at the concrete details of imagining in context, this paper aims to contribute to the emerging literature that is challenging this representational view by offering a relational and radically situated alternative. On the basis of observing architects in the process of making an architectural art installation, we show how to consider imagination not as de-contextualized achievement by an individual but as an opening up to larger-scale “affordances,” i.e. the unfolding possibilities (...) |
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There are few concepts as relevant as that of intentional action in shaping our sense of self and the interaction with the environment. At the same time, few concepts are so elusive. Indeed, both conceptual and neuroscientific accounts of intentional agency have proven to be problematic. On the one hand, most conceptual views struggle in defining how agents can adequately exert control over their actions. On the other hand, neuroscience settles for definitions by exclusion whereby key features of human intentional (...) |
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After more than twenty years of representational debate in the cognitive sciences, anti-representational dynamicism may be seen as offering a rival and radically new kind of explanation of systematicity phenomena. In this paper, I argue that, on the contrary, anti-representational dynamicism must face a version of the old systematicity challenge: either it does not explain systematicity, or else, it is just an implementation of representational theories. To show this, I present a purely behavioral and representation-free account of systematicity. I then (...) |
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The “problem of intentionality” from the vantage point of a representational understanding of mind is explaining what thoughts and beliefs are and how they guide behaviour. From an anti-representationalist perspective, on the other hand, on which cognition itself is taken to be a kind of action, intentionality is a capacity to engage in behaviour that is meaningfully directed toward or about some situation. That these are not in fact competing insights is obscured by the representational/anti-representational framing of the debate. This (...) |
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Susan Hurley's shared circuits model (SCM) rightly begins in action and progresses through a series of layers; but it fails to reach action understanding because it relies on mirroring as a driving force, draws on heavily criticized theories, and neglects the need for shared experience in our grasp of social understanding. |
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Four articles in this issue of topiCS (volume 4, issue 1) argue against a computational approach in cognitive science in favor of a dynamical approach. I concur that the computational approach faces some considerable explanatory challenges. Yet the dynamicists’ proposal that cognition is self-organized seems to only go so far in addressing these challenges. Take, for instance, the hypothesis that cognitive behavior emerges when brain and body (re-)configure to satisfy task and environmental constraints. It is known that for certain systems (...) |
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People cannot understand intentions behind observed actions by direct simulation, because goal inference is highly context dependent. Context dependency is a major source of computational intractability in traditional information-processing models. An embodied embedded view of cognition may be able to overcome this problem, but then the problem needs recognition and explication within the context of the new, layered cognitive architecture. |
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Leech et al. present a connectionist algorithm as a model of (the development) of analogizing, but they do not specify the algorithm's associated computational-level theory, nor its computational complexity. We argue that doing so may be essential for connectionist cognitive models to have full explanatory power and transparency, as well as for assessing their scalability to real-world input domains. |
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