5,154 research outputs found

    Emergence of Self-Organized Symbol-Based Communication \ud in Artificial Creatures

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    In this paper, we describe a digital scenario where we simulated the emergence of self-organized symbol-based communication among artificial creatures inhabiting a \ud virtual world of unpredictable predatory events. In our experiment, creatures are autonomous agents that learn symbolic relations in an unsupervised manner, with no explicit feedback, and are able to engage in dynamical and autonomous communicative interactions with other creatures, even simultaneously. In order to synthesize a behavioral ecology and infer the minimum organizational constraints for the design of our creatures, \ud we examined the well-studied case of communication in vervet monkeys. Our results show that the creatures, assuming the role of sign users and learners, behave collectively as a complex adaptive system, where self-organized communicative interactions play a \ud major role in the emergence of symbol-based communication. We also strive in this paper for a careful use of the theoretical concepts involved, including the concepts of symbol and emergence, and we make use of a multi-level model for explaining the emergence of symbols in semiotic systems as a basis for the interpretation of inter-level relationships in the semiotic processes we are studying

    The perception of emotion in artificial agents

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    Given recent technological developments in robotics, artificial intelligence and virtual reality, it is perhaps unsurprising that the arrival of emotionally expressive and reactive artificial agents is imminent. However, if such agents are to become integrated into our social milieu, it is imperative to establish an understanding of whether and how humans perceive emotion in artificial agents. In this review, we incorporate recent findings from social robotics, virtual reality, psychology, and neuroscience to examine how people recognize and respond to emotions displayed by artificial agents. First, we review how people perceive emotions expressed by an artificial agent, such as facial and bodily expressions and vocal tone. Second, we evaluate the similarities and differences in the consequences of perceived emotions in artificial compared to human agents. Besides accurately recognizing the emotional state of an artificial agent, it is critical to understand how humans respond to those emotions. Does interacting with an angry robot induce the same responses in people as interacting with an angry person? Similarly, does watching a robot rejoice when it wins a game elicit similar feelings of elation in the human observer? Here we provide an overview of the current state of emotion expression and perception in social robotics, as well as a clear articulation of the challenges and guiding principles to be addressed as we move ever closer to truly emotional artificial agents

    Time to start training: A review of cognitive research in sport and proposal for bridging the gap from academia to the field

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    Research demonstrates the importance of perceptual-cognitive skills, such as pattern matching, anticipation, and decision making in numerous sports, including badminton (Abernethy & Russell, 1987), baseball (Burroughs, 1984), basketball (Allard, Graham, & Paarsalu, 1980), handball (Johnson & Raab, 2003), rugby (Lorains, Ball, & MacMahon, 2013), soccer (Ward & Williams, 2003), squash (Abernethy, 1990), tennis (Haskins, 1965), and volleyball (Borgeaud & Abernethy, 1987). While other factors may be important (e.g., visual search patterns), the accuracy and/or speed with which athletes anticipate their opponent’s intentions and/or decide on an appropriate course of action, as assessed in domain-specific tests designed to simulate and represent real-world sporting demands have been shown to be the best and most reliable predictors of skilled performance in the field (see Mann, Williams, Ward, & Janelle, 2007). Moreover, several studies indicate that when training is based on expert models of superior performance, these skills can be improved and transfer to the field (e.g., Fadde, 2009; Ward, Suss, & Basevitch, 2009). In most elite and everyday sports training contexts, expensive research technology (such as eye-tracking equipment) is not always available to practitioners that would help us better understand the cognitive basis of, and ecological constraints of anticipation and decision-making in a way that could be leveraged to tailor training to improve individual and team performance. However, other technologies are now becoming more readily available to support the development of perceptual-cognitive skills. This is particularly timely, because although there is a growing body of research demonstrating the trainability of perceptual-cognitive skills in sport and their transfer to the field, few researchers have attempted to translate this research into accessible and useful training tools for everyday coaches and athletes (for an example, see Belling, Suss, & Ward, 2014). Moreover, research on the validation of such perceptual-cognitive or decision-making skill training tools is startlingly absent from the literature, not just from research on human factors in sport, but in human factors more broadly. In this research, we review what has worked in the past, what can be leveraged by simple and effective tools for accessible devices (e.g., personal computer, tablet), and how powerful these tools can be by reviewing changes in real world performance following their implementation. An NCAA Division 1 baseball team was given access to Axon Sports Cognitive Training for hitting in baseball for the 2013 season. Batting statistics are compared from the 2012 season, without training present, and 2013 season, with training present. The results suggest that batting improved during the season when cognitive training was available to the players. Implications for future research and application are discussed

    A Tale of Two Animats: What does it take to have goals?

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    What does it take for a system, biological or not, to have goals? Here, this question is approached in the context of in silico artificial evolution. By examining the informational and causal properties of artificial organisms ('animats') controlled by small, adaptive neural networks (Markov Brains), this essay discusses necessary requirements for intrinsic information, autonomy, and meaning. The focus lies on comparing two types of Markov Brains that evolved in the same simple environment: one with purely feedforward connections between its elements, the other with an integrated set of elements that causally constrain each other. While both types of brains 'process' information about their environment and are equally fit, only the integrated one forms a causally autonomous entity above a background of external influences. This suggests that to assess whether goals are meaningful for a system itself, it is important to understand what the system is, rather than what it does.Comment: This article is a contribution to the FQXi 2016-2017 essay contest "Wandering Towards a Goal

    Design-led strategy : how to bring design thinking into the art of strategic management

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    Design thinking has emerged as an important way for designers to draw on rich customer insights to enhance their products and services. However, design thinking is now also beginning to influence how corporate managers bring customer data into their day-to-day strategic planning. We call this integration of design thinking into the practice of strategic management “Design-Led Strategy” and show how it complements but extends current design-thinking perspectives. Adopting a strategy-as-practice perspective, this article identifies four archetypal practices that managers can use to strategize with design-thinking content. Its findings provide insight into the practices associated with situating design thinking within organizational practice

    A tale of two densities: Active inference is enactive inference

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    The aim of this paper is to clarify how best to interpret some of the central constructs that underwrite the free-energy principle (FEP) – and its corollary, active inference – in theoretical neuroscience and biology: namely, the role that generative models and variational densities play in this theory. We argue that these constructs have been systematically misrepresented in the literature; because of the conflation between the FEP and active inference, on the one hand, and distinct (albeit closely related) Bayesian formulations, centred on the brain – variously known as predictive processing, predictive coding, or the prediction error minimisation framework. More specifically, we examine two contrasting interpretations of these models: a structural representationalist interpretation and an enactive interpretation. We argue that the structural representationalist interpretation of generative and recognition models does not do justice to the role that these constructs play in active inference under the FEP. We propose an enactive interpretation of active inference – what might be called enactive inference. In active inference under the FEP, the generative and recognition models are best cast as realising inference and control – the self-organising, belief-guided selection of action policies – and do not have the properties ascribed by structural representationalists

    Possibilities for pedagogy in Further Education: Harnessing the abundance of literacy

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    In this report, it is argued that the most salient factor in the contemporary communicative landscape is the sheer abundance and diversity of possibilities for literacy, and that the extent and nature of students' communicative resources is a central issue in education. The text outlines the conceptual underpinnings of the Literacies for Learning in Further Education project in a social view of literacy, and the associated research design, methodology and analytical framework. It elaborates on the notion of the abundance of literacies in students' everyday lives, and on the potential for harnessing these as resources for the enhancement of learning. It provides case studies of changes in practice that have been undertaken by further education staff in order to draw upon students' everyday literacy practices on Travel and Tourism and Multimedia courses. It ends with some of the broad implications for conceptualising learning that arise from researching through the lens of literacy practices
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