23 research outputs found

    Annotated Bibliography: Anticipation

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    EVENT COREFERENCE RESOLUTION

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    Ph.DDOCTOR OF PHILOSOPH

    Advances in Artificial Intelligence: Models, Optimization, and Machine Learning

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    The present book contains all the articles accepted and published in the Special Issue “Advances in Artificial Intelligence: Models, Optimization, and Machine Learning” of the MDPI Mathematics journal, which covers a wide range of topics connected to the theory and applications of artificial intelligence and its subfields. These topics include, among others, deep learning and classic machine learning algorithms, neural modelling, architectures and learning algorithms, biologically inspired optimization algorithms, algorithms for autonomous driving, probabilistic models and Bayesian reasoning, intelligent agents and multiagent systems. We hope that the scientific results presented in this book will serve as valuable sources of documentation and inspiration for anyone willing to pursue research in artificial intelligence, machine learning and their widespread applications

    Urban Informatics

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    This open access book is the first to systematically introduce the principles of urban informatics and its application to every aspect of the city that involves its functioning, control, management, and future planning. It introduces new models and tools being developed to understand and implement these technologies that enable cities to function more efficiently – to become ‘smart’ and ‘sustainable’. The smart city has quickly emerged as computers have become ever smaller to the point where they can be embedded into the very fabric of the city, as well as being central to new ways in which the population can communicate and act. When cities are wired in this way, they have the potential to become sentient and responsive, generating massive streams of ‘big’ data in real time as well as providing immense opportunities for extracting new forms of urban data through crowdsourcing. This book offers a comprehensive review of the methods that form the core of urban informatics from various kinds of urban remote sensing to new approaches to machine learning and statistical modelling. It provides a detailed technical introduction to the wide array of tools information scientists need to develop the key urban analytics that are fundamental to learning about the smart city, and it outlines ways in which these tools can be used to inform design and policy so that cities can become more efficient with a greater concern for environment and equity

    Urban Informatics

    Get PDF
    This open access book is the first to systematically introduce the principles of urban informatics and its application to every aspect of the city that involves its functioning, control, management, and future planning. It introduces new models and tools being developed to understand and implement these technologies that enable cities to function more efficiently – to become ‘smart’ and ‘sustainable’. The smart city has quickly emerged as computers have become ever smaller to the point where they can be embedded into the very fabric of the city, as well as being central to new ways in which the population can communicate and act. When cities are wired in this way, they have the potential to become sentient and responsive, generating massive streams of ‘big’ data in real time as well as providing immense opportunities for extracting new forms of urban data through crowdsourcing. This book offers a comprehensive review of the methods that form the core of urban informatics from various kinds of urban remote sensing to new approaches to machine learning and statistical modelling. It provides a detailed technical introduction to the wide array of tools information scientists need to develop the key urban analytics that are fundamental to learning about the smart city, and it outlines ways in which these tools can be used to inform design and policy so that cities can become more efficient with a greater concern for environment and equity

    Urban Informatics

    Get PDF
    This open access book is the first to systematically introduce the principles of urban informatics and its application to every aspect of the city that involves its functioning, control, management, and future planning. It introduces new models and tools being developed to understand and implement these technologies that enable cities to function more efficiently – to become ‘smart’ and ‘sustainable’. The smart city has quickly emerged as computers have become ever smaller to the point where they can be embedded into the very fabric of the city, as well as being central to new ways in which the population can communicate and act. When cities are wired in this way, they have the potential to become sentient and responsive, generating massive streams of ‘big’ data in real time as well as providing immense opportunities for extracting new forms of urban data through crowdsourcing. This book offers a comprehensive review of the methods that form the core of urban informatics from various kinds of urban remote sensing to new approaches to machine learning and statistical modelling. It provides a detailed technical introduction to the wide array of tools information scientists need to develop the key urban analytics that are fundamental to learning about the smart city, and it outlines ways in which these tools can be used to inform design and policy so that cities can become more efficient with a greater concern for environment and equity

    Interaction dynamics and autonomy in cognitive systems

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    The concept of autonomy is of crucial importance for understanding life and cognition. Whereas cellular and organismic autonomy is based in the self-production of the material infrastructure sustaining the existence of living beings as such, we are interested in how biological autonomy can be expanded into forms of autonomous agency, where autonomy as a form of organization is extended into the behaviour of an agent in interaction with its environment (and not its material self-production). In this thesis, we focus on the development of operational models of sensorimotor agency, exploring the construction of a domain of interactions creating a dynamical interface between agent and environment. We present two main contributions to the study of autonomous agency: First, we contribute to the development of a modelling route for testing, comparing and validating hypotheses about neurocognitive autonomy. Through the design and analysis of specific neurodynamical models embedded in robotic agents, we explore how an agent is constituted in a sensorimotor space as an autonomous entity able to adaptively sustain its own organization. Using two simulation models and different dynamical analysis and measurement of complex patterns in their behaviour, we are able to tackle some theoretical obstacles preventing the understanding of sensorimotor autonomy, and to generate new predictions about the nature of autonomous agency in the neurocognitive domain. Second, we explore the extension of sensorimotor forms of autonomy into the social realm. We analyse two cases from an experimental perspective: the constitution of a collective subject in a sensorimotor social interactive task, and the emergence of an autonomous social identity in a large-scale technologically-mediated social system. Through the analysis of coordination mechanisms and emergent complex patterns, we are able to gather experimental evidence indicating that in some cases social autonomy might emerge based on mechanisms of coordinated sensorimotor activity and interaction, constituting forms of collective autonomous agency

    Multimodal knowledge integration for object detection and visual reasoning

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    We humans still perceive and reason in a different way than artificial intelligence models. We witness, we listen, we touch, we understand the world via multi-modal sensing, while machine models rely only on a single or a few modalities and ignore abundant information. In this thesis, we explore techniques for reducing the perception gap between machines and humans and focus on two families of tasks, reasoning and detection. First, we incorporate information from text, audio, motion, external knowledge bases, for training computer vision models. We find that data inputs from more extensive channels provide complementary information to improve models. Second, we study how multimodal inputs can be fully utilized. We argue that most existing deep learning methods are prone to pay too large attention to shallow patterns in the input features, which causes the resulting models to be biased. We propose robust training to overcome the issue. Third, we extend the benefits of multi-modal information to the supervision signals instead of the inputs, by learning a weakly supervised detection model from the natural supervision of textual captions or audio narrations. With the help of NLP constituency parsing, it is possible to extract structural knowledges from the captions and narrations, hence determines the entities and relations of visual objects

    Non-Equilibrium Social Science and Policy

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    The overall aim of this book, an outcome of the European FP7 FET Open NESS project, is to contribute to the ongoing effort to put the quantitative social sciences on a proper footing for the 21st century. A key focus is economics, and its implications on policy making, where the still dominant traditional approach increasingly struggles to capture the economic realities we observe in the world today - with vested interests getting too often in the way of real advances. Insights into behavioral economics and modern computing techniques have made possible both the integration of larger information sets and the exploration of disequilibrium behavior. The domain-based chapters of this work illustrate how economic theory is the only branch of social sciences which still holds to its old paradigm of an equilibrium science - an assumption that has already been relaxed in all related fields of research in the light of recent advances in complex and dynamical systems theory and related data mining. The other chapters give various takes on policy and decision making in this context. Written in nontechnical style throughout, with a mix of tutorial and essay-like contributions, this book will benefit all researchers, scientists, professionals and practitioners interested in learning about the 'thinking in complexity' to understand how socio-economic systems really work

    Non-Equilibrium Social Science and Policy: Introduction and Essays on New and Changing Paradigms in Socio-Economic Thinking

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    Data-driven Science, Modeling and Theory Building; Methodology of the Social Sciences; Economic Theory/Quantitative Economics/Mathematical Methods; Operation Research/Decision Theory; Complexit
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