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  • 1.
    Lindblom, Jessica
    et al.
    University of Skövde, School of Humanities and Informatics.
    Ziemke, Tom
    University of Skövde, School of Humanities and Informatics.
    The social body in motion: cognitive development in infants and androids2006In: Connection science (Print), ISSN 0954-0091, E-ISSN 1360-0494, Vol. 18, no 4, p. 333-346Article in journal (Refereed)
    Abstract [en]

    During the past two decades, embodiment has become an important concept in many areas of cognitive science, but so far there is no common understanding of what constitutes embodied cognition and what kind of body an artificial humanlike cognizer would require. Work in embodied artificial intelligence and robotics has addressed, to some degree, what kind of bodily implementation is necessary for embodied cognition, but crucial factors such as the role of social interaction and the 'body-in-motion' have still not received much attention. We argue that, in the human child, the interplay of social scaffolding and self-induced locomotion is fundamental to the development of joint attention and a 'self'. Furthermore, we discuss the implications of the social dynamics of bodily experience for android science. We argue that keeping scientific and engineering perspectives apart, but also understanding their relation, is important for clarifying the objectives of android science.

  • 2.
    Lowe, Robert
    et al.
    University of Skövde, School of Humanities and Informatics. University of Skövde, The Informatics Research Centre.
    Humphries, Mark
    Univ Sheffield, Dept Psychol, Sheffield S10 2TN, S Yorkshire, England.
    Ziemke, Tom
    University of Skövde, School of Humanities and Informatics. University of Skövde, The Informatics Research Centre.
    The dual-route hypothesis: evaluating a neurocomputational model of fear conditioning in rats2009In: Connection science (Print), ISSN 0954-0091, E-ISSN 1360-0494, Vol. 21, no 1, p. 15-37Article in journal (Refereed)
    Abstract [en]

     Research on the neural bases of emotion raises much controversy and few quantitative models exist that can help address the issues raised. Here we replicate and dissect one of those models, Armony and colleagues’neurocomputational model of fear conditioning, which is based on LeDoux’s dual-route hypothesis regarding the rat fear circuitry. The importance of the model’s modular abstraction of the neuroanatomy, its use of population coding, and in particular the interplay between thalamo-amygdala and thalamo-cortical pathways are tested. We show that a trivially minimal version of the model can produce conditioning to a reinforced stimulus without recourse to the dual pathway structure, but a modification of the original model, which nevertheless preserves the thalamo-amygdala and (reduced) thalamo-cortical pathways, enables stronger conditioning to a conditioned stimulus. Implications for neurocomputational modelling approaches are discussed.

     

  • 3.
    Lowe, Robert
    et al.
    University of Skövde, School of Humanities and Informatics. University of Skövde, The Informatics Research Centre.
    Ziemke, Tom
    University of Skövde, School of Humanities and Informatics. University of Skövde, The Informatics Research Centre.
    Towards a cognitive robotics methodology for reward-based decision-making: dynamical systems modelling of the Iowa Gambling Task2010In: Connection science (Print), ISSN 0954-0091, E-ISSN 1360-0494, Vol. 22, no 3, p. 247-289Article in journal (Refereed)
    Abstract [en]

    The somatic marker hypothesis (SMH) posits that the role of emotions and mental states in decision-making manifests through bodily responses to stimuli of import to the organism’s welfare. The Iowa Gambling Task (IGT), proposed by Bechara and Damasio in the mid-1990s, has provided the major source of empirical validation to the role of somatic markers in the service of flexible and cost-effective decision-making in humans. In recent years the IGT has been the subject of much criticism concerning: (1) whether measures of somatic markers reveal that they are important for decision-making as opposed to behaviour preparation; (2) the underlying neural substrate posited as critical to decision-making of the type relevant to the task; and (3) aspects of the methodological approach used, particularly on the canonical version of the task. In this paper, a cognitive robotics methodology is proposed to explore a dynamical systems approach as it applies to the neural computation of reward-based learning and issues concerning embodiment. This approach is particularly relevant in light of a strongly emerging alternative hypothesis to the SMH, the reversal learning hypothesis, which links, behaviourally and neurocomputationally, a number of more or less complex reward-based decision-making tasks, including the ‘A-not-B’ task – already subject to dynamical systems investigations with a focus on neural activation dynamics. It is also suggested that the cognitive robotics methodology may be used to extend systematically the IGT benchmark to more naturalised, but nevertheless controlled, settings that might better explore the extent to which the SMH, and somatic states per se, impact on complex decision-making.

  • 4.
    Morse, Anthony F.
    et al.
    University of Skövde, School of Humanities and Informatics. University of Skövde, The Informatics Research Centre.
    Lowe, Robert
    University of Skövde, School of Humanities and Informatics. University of Skövde, The Informatics Research Centre.
    Ziemke, Tom
    University of Skövde, School of Humanities and Informatics. University of Skövde, The Informatics Research Centre.
    Manipulating space: modelling the role of transient dynamics in inattentional blindness2009In: Connection science (Print), ISSN 0954-0091, E-ISSN 1360-0494, Vol. 21, no 4, p. 275-296Article in journal (Refereed)
    Abstract [en]

    According to Noë´s enactive theory of perception, sensorimotor knowledge allows us to predict the sensory outcomes of our actions. This paper suggests that tuning input filters with such predictions may be the cause of sustained inattentional blindness. Most models of learning capture statistically salient regularities in and between data streams. Such analysis is, however, severely limited by both the problem of marginal regularity and the credit assignment problem. A neurocomputational reservoir system can be used to alleviate these problems without training by enhancing the separability of regularities in input streams. However, as the regularities made separable vary with the state of the reservoir, feedback in the form of predictions of future sensory input can both enchance expected discriminations and hinder unanticipated ones. This renders the model blind to features not made separable in the regions of state space the reservoir in manipulated towards. This is demonstrated in a computational model of sustained inattentional blindness, leading to predictions about human behaviour that have yet to be tested.

  • 5.
    Ziemke, Tom
    et al.
    University of Skövde, School of Humanities and Informatics. University of Skövde, The Informatics Research Centre.
    Lowe, Robert
    University of Skövde, School of Humanities and Informatics. University of Skövde, The Informatics Research Centre.
    Morse, Anthony
    Univ Plymouth, Plymouth PL4 8AA, Devon, England.
    Affective robotics - modelling emotion and motivation2010In: Connection science (Print), ISSN 0954-0091, E-ISSN 1360-0494, Vol. 22, no 3, p. 193-195Article in journal (Other academic)
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