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  1. Richard P. Cooper & David Peebles (2015). Beyond Single‐Level Accounts: The Role of Cognitive Architectures in Cognitive Scientific Explanation. Topics in Cognitive Science 7 (2):243-258.
    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 (...)
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  2. Livia Freier, Richard P. Cooper & Denis Mareschal (2015). The Planning and Execution of Natural Sequential Actions in the Preschool Years. Cognition 144:58-66.
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  3. David Peebles & Richard P. Cooper (2015). Thirty Years After Marr's Vision: Levels of Analysis in Cognitive Science. Topics in Cognitive Science 7 (2):187-190.
    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 (...)
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  4. Richard P. Cooper, Nicolas Ruh & Denis Mareschal (2014). The Goal Circuit Model: A Hierarchical Multi‐Route Model of the Acquisition and Control of Routine Sequential Action in Humans. Cognitive Science 38 (2):244-274.
    Human control of action in routine situations involves a flexible interplay between (a) task-dependent serial ordering constraints; (b) top-down, or intentional, control processes; and (c) bottom-up, or environmentally triggered, affordances. In addition, the interaction between these influences is modulated by learning mechanisms that, over time, appear to reduce the need for top-down control processes while still allowing those processes to intervene at any point if necessary or if desired. We present a model of the acquisition and control of goal-directed action (...)
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  5. Richard P. Cooper, Caroline Catmur & Cecilia Heyes (2013). Are Automatic Imitation and Spatial Compatibility Mediated by Different Processes? Cognitive Science 37 (4):605-630.
    Automatic imitation or “imitative compatibility” is thought to be mediated by the mirror neuron system and to be a laboratory model of the motor mimicry that occurs spontaneously in naturalistic social interaction. Imitative compatibility and spatial compatibility effects are known to depend on different stimulus dimensions—body movement topography and relative spatial position. However, it is not yet clear whether these two types of stimulus–response compatibility effect are mediated by the same or different cognitive processes. We present an interactive activation model (...)
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  6. Richard P. Cooper, Caroline Catmur & Cecilia Heyes (2013). Neither Shaken nor Stirred: Reply to Bertenthal and Scheutz. Cognitive Science 37 (4):642-645.
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  7. Richard P. Cooper (2011). Complementary Perspectives on Cognitive Control. Topics in Cognitive Science 3 (2):208-211.
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  8. Richard P. Cooper (2010). Cognitive Control: Componential or Emergent? Topics in Cognitive Science 2 (4):598-613.
    The past 25 years have witnessed an increasing awareness of the importance of cognitive control in the regulation of complex behavior. It now sits alongside attention, memory, language, and thinking as a distinct domain within cognitive psychology. At the same time it permeates each of these sibling domains. This introduction reviews recent work on cognitive control in an attempt to provide a context for the fundamental question addressed within this topic: Is cognitive control to be understood as resulting from the (...)
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  9. Richard P. Cooper & Tim Shallice (2010). Cognitive Neuroscience: The Troubled Marriage of Cognitive Science and Neuroscience. Topics in Cognitive Science 2 (3):398-406.
    We discuss the development of cognitive neuroscience in terms of the tension between the greater sophistication in cognitive concepts and methods of the cognitive sciences and the increasing power of more standard biological approaches to understanding brain structure and function. There have been major technological developments in brain imaging and advances in simulation, but there have also been shifts in emphasis, with topics such as thinking, consciousness, and social cognition becoming fashionable within the brain sciences. The discipline has great promise (...)
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  10. Eddy J. Davelaar & Richard P. Cooper (2010). Modelling the Correlation Between Two Putative Inhibition Tasks: An Analytic Approach. In S. Ohlsson & R. Catrambone (eds.), Proceedings of the 32nd Annual Conference of the Cognitive Science Society. Cognitive Science Society
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  11. Robert Leech, Denis Mareschal & Richard P. Cooper (2008). Analogy as Relational Priming: A Developmental and Computational Perspective on the Origins of a Complex Cognitive Skill. Behavioral and Brain Sciences 31 (4):357-378.
    The development of analogical reasoning has traditionally been understood in terms of theories of adult competence. This approach emphasizes structured representations and structure mapping. In contrast, we argue that by taking a developmental perspective, analogical reasoning can be viewed as the product of a substantially different cognitive ability – relational priming. To illustrate this, we present a computational (here connectionist) account where analogy arises gradually as a by-product of pattern completion in a recurrent network. Initial exposure to a situation primes (...)
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  12. Robert Leech, Denis Mareschal & Richard P. Cooper (2008). Growing Cognition From Recycled Parts. Behavioral and Brain Sciences 31 (4):401-414.
    In this response, we reiterate the importance of development (both ontogenetic and phylogenetic) in the understanding of a complex cognitive skill – analogical reasoning. Four key questions structure the response: Does relational priming exist, and is it sufficient for analogy? What do we mean by relations as transformations? Could all or any relations be represented as transformations? And what about the challenge of more complex analogies? In addressing these questions we bring together a number of supportive commentaries, strengthening our emergentist (...)
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  13. Richard P. Cooper (2007). The Role of Falsification in the Development of Cognitive Architectures: Insights From a Lakatosian Analysis. Cognitive Science 31 (3):509-533.
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  14. Richard P. Cooper (2006). Cognitive Architectures as Lakatosian Research Programs: Two Case Studies. Philosophical Psychology 19 (2):199-220.
    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 (...)
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  15. Richard P. Cooper (2003). Mechanisms for the Generation and Regulation of Sequential Behaviour. Philosophical Psychology 16 (3):389 – 416.
    A critical aspect of much human behaviour is the generation and regulation of sequential activities. Such behaviour is seen in both naturalistic settings such as routine action and language production and laboratory tasks such as serial recall and many reaction time experiments. There are a variety of computational mechanisms that may support the generation and regulation of sequential behaviours, ranging from those underlying Turing machines to those employed by recurrent connectionist networks. This paper surveys a range of such mechanisms, together (...)
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  16. Richard P. Cooper (2002). Two Closely Related Simulations Provide Weak Limits on Residual Normality. Behavioral and Brain Sciences 25 (6):754-755.
    Thomas & Karmiloff-Smith (T&K-S) correctly identify Residual Normality (RN) as a critical assumption of some theorising about mental structure within developmental psychology. However, their simulations provide only weak support for the conditions under which RN may occur because they explore closely related architectures that share a learning algorithm. It is suggested that more work is required to establish the limits of RN.
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