41 resultados para KOLMOGOROV COMPLEXITY

em Aston University Research Archive


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The assertion about the unique 'complexity' or the peculiarly intricate character of social phenomena has, at least within sociology, a long, venerable and virtually uncontested tradition. At the turn of the last century, classical social theorists, for example, Georg Simmel and Emile Durkheim, made prominent and repeated reference to this attribute of the subject matter of sociology and the degree to which it complicates, even inhibits the development and application of social scientific knowledge. Our paper explores the origins, the basis and the consequences of this assertion and asks in particular whether the classic complexity assertion still deserves to be invoked in analyses that ask about the production and the utilization of social scientific knowledge in modern society. We present John Maynard Keynes' economic theory and its practical applications as an illustration. We conclude that the practical value of social scientific knowledge is not dependent on a faithful, in the sense of complete, representation of social reality. Instead, social scientific knowledge that wants to optimize its practicality has to attend and attach itself to elements of social situations that can be altered or are actionable.

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In this paper we consider four alternative approaches to complexity control in feed-forward networks based respectively on architecture selection, regularization, early stopping, and training with noise. We show that there are close similarities between these approaches and we argue that, for most practical applications, the technique of regularization should be the method of choice.

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The Vapnik-Chervonenkis (VC) dimension is a combinatorial measure of a certain class of machine learning problems, which may be used to obtain upper and lower bounds on the number of training examples needed to learn to prescribed levels of accuracy. Most of the known bounds apply to the Probably Approximately Correct (PAC) framework, which is the framework within which we work in this paper. For a learning problem with some known VC dimension, much is known about the order of growth of the sample-size requirement of the problem, as a function of the PAC parameters. The exact value of sample-size requirement is however less well-known, and depends heavily on the particular learning algorithm being used. This is a major obstacle to the practical application of the VC dimension. Hence it is important to know exactly how the sample-size requirement depends on VC dimension, and with that in mind, we describe a general algorithm for learning problems having VC dimension 1. Its sample-size requirement is minimal (as a function of the PAC parameters), and turns out to be the same for all non-trivial learning problems having VC dimension 1. While the method used cannot be naively generalised to higher VC dimension, it suggests that optimal algorithm-dependent bounds may improve substantially on current upper bounds.

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The assertion about the peculiarly intricate and complex character of social phenomena has, in much of social discourse, a virtually uncontested tradition. A significant part of the premise about the complexity of social phenomena is the conviction that it complicates, perhaps even inhibits the development and application of social scientific knowledge. Our paper explores the origins, the basis and the consequences of this assertion and asks in particular whether the classic complexity assertion still deserves to be invoked in analyses that ask about the production and the utilization of social scientific knowledge in modern society. We refer to one of the most prominent and politically influential social scientific theories, John Maynard Keynes' economic theory as an illustration. We conclude that, the practical value of social scientific knowledge is not necessarily dependent on a faithful, in the sense of complete, representation of (complex) social reality. Practical knowledge is context sensitive if not project bound. Social scientific knowledge that wants to optimize its practicality has to attend and attach itself to elements of practical social situations that can be altered or are actionable by relevant actors. This chapter represents an effort to re-examine the relation between social reality, social scientific knowledge and its practical application. There is a widely accepted view about the potential social utility of social scientific knowledge that invokes the peculiar complexity of social reality as an impediment to good theoretical comprehension and hence to its applicability.

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The purpose of this paper is to demonstrate the existence of a strong and significant effect of complexity in aphasia independent from other variables including length. Complexity was found to be a strong and significant predictor of accurate repetition in a group of 13 Italian aphasic patients when it was entered in a regression equation either simultaneously or after a large number of other variables. Significant effects were found both when complexity was measured in terms of number of complex onsets (as in a recent paper by Nickels & Howard, 2004) and when it was measured in a more comprehensive way. Significant complexity effects were also found with matched lists contrasting simple and complex words and in analyses of errors. Effects of complexity, however, were restricted to patients with articulatory difficulties. Reasons for this association and for the lack of significant results in Nickels and Howard (2004) are discussed. © 2005 Psychology Press Ltd.

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We present an implementation of the domain-theoretic Picard method for solving initial value problems (IVPs) introduced by Edalat and Pattinson [1]. Compared to Edalat and Pattinson's implementation, our algorithm uses a more efficient arithmetic based on an arbitrary precision floating-point library. Despite the additional overestimations due to floating-point rounding, we obtain a similar bound on the convergence rate of the produced approximations. Moreover, our convergence analysis is detailed enough to allow a static optimisation in the growth of the precision used in successive Picard iterations. Such optimisation greatly improves the efficiency of the solving process. Although a similar optimisation could be performed dynamically without our analysis, a static one gives us a significant advantage: we are able to predict the time it will take the solver to obtain an approximation of a certain (arbitrarily high) quality.

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Quality management is dominated by rational paradigms for the measurement and management of quality, but these paradigms start to “break down”, when faced with the inherent complexity of managing quality in intensely competitive changing environments. In this article, the various theoretical strategy paradigms employed to manage quality are reviewed and the advantages and limitations of these paradigms are highlighted. A major implication of this review is that when faced with complexity, an ideological stance to any single strategy paradigm for the management of quality is ineffective. A case study is used to demonstrate the need for an integrative multi-paradigm approach to the management of quality as complexity increases.

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DUE TO COPYRIGHT RESTRICTIONS ONLY AVAILABLE FOR CONSULTATION AT ASTON UNIVERSITY LIBRARY WITH PRIOR ARRANGEMENT

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The thesis contributes to the evolving process of moving the study of Complexity from the arena of metaphor to something real and operational. Acknowledging this phenomenon ultimately changes the underlying assumptions made about working environments and leadership; organisations are dynamic and so should their leaders be. Dynamic leaders are behaviourally complex. Behavioural Complexity is a product of behavioural repertoire - range of behaviours; and behavioural differentiation - where effective leaders apply appropriate behaviour to the demands of the situation. Behavioural Complexity was operationalised using the Competing Values Framework (CVF). The CVF is a measure that captures the extent to which leaders demonstrate four behaviours on four quadrants: Control, Compete, Collaborate and Create, which are argued to be critical to all types of organisational leadership. The results provide evidence to suggest Behavioural Complexity is an enabler of leadership effectiveness; Organisational Complexity (captured using a new measure developed in the thesis) moderates Behavioural Complexity and leadership effectiveness; and leadership training supports Behavioural Complexity in contributing to leadership effectiveness. Most definitions of leadership come down to changing people’s behaviour. Such definitions have contributed to a popularity of focus in leadership research intent on exploring how to elicit change in others when maybe some of the popularity of attention should have been on eliciting change in the leader them self. It is hoped that this research will provoke interest into the factors that cause behavioural change in leaders that in turn enable leadership effectiveness and in doing so contribute to a better understanding of leadership in organisations.

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Although advertising is pervasive in our daily, it proves to be not necessarily efficient all the times due to bad conditions or bad contexts of reception. Indeed, the communication process might be jeopardized at its very last stage because of advertising exposure quality. However critical it may be, ad exposure quality is not very much examined by researchers or practitioners. In this paper, we investigate how tiredness combined with ad complexity might influence the way consumers extract and process ad elements. Investigating tiredness is useful because it is a common daily state experienced by everyone at various moments of the day. And although it might drastically alter ad reception, it has not been studied in advertising for the moment. In this regards, we observe eye movement patterns of consumers viewing simple or complex advertisements being tired or not. We surprisingly find that tired subjects viewing complex ads don’t adopt a lessening effort visual strategy. They rather use a resource demanding one. We assume that the Sustained Attention strategy occurring is a kind of adaptive strategy allowing to deal with an anticipated lack of resource.