169,198 research outputs found

    Bio-inspired Mechanisms for Artificial Self-organised Systems

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    Research on self-organization tries to describe and explain forms, complex patterns and behaviours that arise from a collection of entities without an external organizer. As researchers in artificial systems, our aim is not to mimic self-organizing phenomena arising in Nature, but to understand and to control underlying mechanisms allowing desired emergence of forms, complex patterns and behaviours. In this paper we analyze three forms of self-organization: stigmergy, reinforcement mechanisms and cooperation. For each forms of self-organisation, we present a case study to show how we transposed it to some artificial systems and then analyse the strengths and weaknesses of such an approach

    Antisocial behaviour and the vulnerable public

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    Key to understanding the emergence of antisocial behavior legislation in the UK is the concept of diminished subjectivity, the emergence of an insecure elite guided by a precautionary principle of safety, and the construction and engagement with a universalised vulnerable public. As such this chapter attempts to explain how the demoralisation of the Cold War political framework resulted in a new relationship developing between previously political and moral subjects and the (post) modern elite. Central to this is the transformation of the robust liberal subject into a newly conceptualised vulnerable individual. Helped by the decline of moral conservatism and the collapse of political radicalism the active individual and collective were reimagined as victims of crime and vulnerable groups. Once reconceptualised in this way, the more fragmented public of the post-Cold War world, were engaged with through the emotion of fear and the therapeutic state stepped in to regulate an increasing array of behaviours, actions and speech that were previously not seen as criminal or in need of state control. The outcome is the institutionalisation of an asocial, fragile character type as the new norm for society by an insecure state that keeps us all at a safe distance from one another

    Bioelectrical understanding and engineering of cell biology

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    The last five decades of molecular and systems biology research have provided unprecedented insights into the molecular and genetic basis of many cellular processes. Despite these insights, however, it is arguable that there is still only limited predictive understanding of cell behaviours. In particular, the basis of heterogeneity in single-cell behaviour and the initiation of many different metabolic, transcriptional or mechanical responses to environmental stimuli remain largely unexplained. To go beyond the status quo, the understanding of cell behaviours emerging from molecular genetics must be complemented with physical and physiological ones, focusing on the intracellular and extracellular conditions within and around cells. Here, we argue that such a combination of genetics, physics and physiology can be grounded on a bioelectrical conceptualization of cells. We motivate the reasoning behind such a proposal and describe examples where a bioelectrical view has been shown to, or can, provide predictive biological understanding. In addition, we discuss how this view opens up novel ways to control cell behaviours by electrical and electrochemical means, setting the stage for the emergence of bioelectrical engineering

    Agent-based modelling in synthetic biology

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    Biological systems exhibit complex behaviours that emerge at many different levels of organization. These span the regulation of gene expression within single cells to the use of quorum sensing to co-ordinate the action of entire bacterial colonies. Synthetic biology aims to make the engineering of biology easier, offering an opportunity to control natural systems and develop new synthetic systems with useful prescribed behaviours. However, in many cases, it is not understood how individual cells should be programmed to ensure the emergence of a required collective behaviour. Agent-based modelling aims to tackle this problem, offering a framework in which to simulate such systems and explore cellular design rules. In this article, I review the use of agent-based models in synthetic biology, outline the available computational tools, and provide details on recently engineered biological systems that are amenable to this approach. I further highlight the challenges facing this methodology and some of the potential future directions

    HRM and innovation:looking across levels

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    Studies are starting to explore the role of HRM in fostering organizational innovation but empirical evidence remains contradictory and theory fragmented. This is partly because extant literature by and large adopts a unitary level of analysis, rather than reflecting on the multi-level demands that innovation presents. Building on an emergent literature focused on HRM’s role in shaping innovation, we shed light on the question of whether, and how, HRM might influence employees’ innovative behaviours in the direction of strategically important goals. Drawing upon institutional theory, our contributions are three-fold: to bring out the effect of two discrete HRM configurations- one underpinned by a control and the other by an entrepreneurial ethos, on attitudes and behaviours at the individual level; to reflect the way in which employee innovative behaviours arising from these HRM configurations coalesce to shape higher-level phenomena, such as organizational-level innovation; and to bring out two distinct patterns of bottom-up emergence, one driven primarily by composition and the other by both composition and compilation

    Towards adaptive multi-robot systems: self-organization and self-adaptation

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    Dieser Beitrag ist mit Zustimmung des Rechteinhabers aufgrund einer (DFG geförderten) Allianz- bzw. Nationallizenz frei zugänglich.This publication is with permission of the rights owner freely accessible due to an Alliance licence and a national licence (funded by the DFG, German Research Foundation) respectively.The development of complex systems ensembles that operate in uncertain environments is a major challenge. The reason for this is that system designers are not able to fully specify the system during specification and development and before it is being deployed. Natural swarm systems enjoy similar characteristics, yet, being self-adaptive and being able to self-organize, these systems show beneficial emergent behaviour. Similar concepts can be extremely helpful for artificial systems, especially when it comes to multi-robot scenarios, which require such solution in order to be applicable to highly uncertain real world application. In this article, we present a comprehensive overview over state-of-the-art solutions in emergent systems, self-organization, self-adaptation, and robotics. We discuss these approaches in the light of a framework for multi-robot systems and identify similarities, differences missing links and open gaps that have to be addressed in order to make this framework possible

    To boldly go:an occam-π mission to engineer emergence

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    Future systems will be too complex to design and implement explicitly. Instead, we will have to learn to engineer complex behaviours indirectly: through the discovery and application of local rules of behaviour, applied to simple process components, from which desired behaviours predictably emerge through dynamic interactions between massive numbers of instances. This paper describes a process-oriented architecture for fine-grained concurrent systems that enables experiments with such indirect engineering. Examples are presented showing the differing complex behaviours that can arise from minor (non-linear) adjustments to low-level parameters, the difficulties in suppressing the emergence of unwanted (bad) behaviour, the unexpected relationships between apparently unrelated physical phenomena (shown up by their separate emergence from the same primordial process swamp) and the ability to explore and engineer completely new physics (such as force fields) by their emergence from low-level process interactions whose mechanisms can only be imagined, but not built, at the current time

    Education and transfer of water competencies: An ecological dynamics approach

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    © The Author(s) 2020. To cope in various aquatic environments (i.e. swimming pools, lakes, rivers, oceans), learners require a wide repertoire of self-regulatory behaviours such as awareness of obstacles and water properties, floating and moving from point to point with different strokes, decision making, emotional control and breathing efficiently. By experiencing different learning situations in stable indoor pool environments, it is assumed that children strengthen aquatic competencies that should be transferable to functioning in open water environments, where prevalence of drowning is high. However, this fundamental assumption may be misleading. Here, we propose the application of a clear, related methodology and theoretical framework that could be useful to help physical education curriculum specialists (re)shape and (re)design appropriate aquatic learning situations to facilitate better transfer of learning. We discuss the need for more representativeness in a learning environment, proposing how the many different task and environmental constraints on aquatic actions may bound the emergence of functional, self-regulatory behaviours in learners. Ideas in ecological dynamics suggest that physical educators should design learning environments that offer a rich landscape of opportunities for action for learners. As illustration, three practice interventions are described for developing functional and transferrable skills in indoor aquatic environments. It is important that aquatic educators focus not just upon ‘learning to swim’, but particularly on relevant transferable skills and self-regulatory behaviours deemed necessary for functioning in dynamic, outdoor aquatic environments

    Education and transfer of water competencies: An ecological dynamics approach

    Get PDF
    © The Author(s) 2020. To cope in various aquatic environments (i.e. swimming pools, lakes, rivers, oceans), learners require a wide repertoire of self-regulatory behaviours such as awareness of obstacles and water properties, floating and moving from point to point with different strokes, decision making, emotional control and breathing efficiently. By experiencing different learning situations in stable indoor pool environments, it is assumed that children strengthen aquatic competencies that should be transferable to functioning in open water environments, where prevalence of drowning is high. However, this fundamental assumption may be misleading. Here, we propose the application of a clear, related methodology and theoretical framework that could be useful to help physical education curriculum specialists (re)shape and (re)design appropriate aquatic learning situations to facilitate better transfer of learning. We discuss the need for more representativeness in a learning environment, proposing how the many different task and environmental constraints on aquatic actions may bound the emergence of functional, self-regulatory behaviours in learners. Ideas in ecological dynamics suggest that physical educators should design learning environments that offer a rich landscape of opportunities for action for learners. As illustration, three practice interventions are described for developing functional and transferrable skills in indoor aquatic environments. It is important that aquatic educators focus not just upon ‘learning to swim’, but particularly on relevant transferable skills and self-regulatory behaviours deemed necessary for functioning in dynamic, outdoor aquatic environments
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