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Titlebook: Artificial Intelligence: Theories, Models and Applications; 5th Hellenic Confere John Darzentas,George A. Vouros,Argyris Arnellos Conferenc

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發(fā)表于 2025-3-21 17:54:09 | 只看該作者 |倒序瀏覽 |閱讀模式
期刊全稱Artificial Intelligence: Theories, Models and Applications
期刊簡稱5th Hellenic Confere
影響因子2023John Darzentas,George A. Vouros,Argyris Arnellos
視頻videohttp://file.papertrans.cn/163/162580/162580.mp4
學科分類Lecture Notes in Computer Science
圖書封面Titlebook: Artificial Intelligence: Theories, Models and Applications; 5th Hellenic Confere John Darzentas,George A. Vouros,Argyris Arnellos Conferenc
影響因子Artificial intelligence (AI) is a dynamic field that is constantly expanding into new application areas, discovering new research challenges and facilitating the devel- ment of innovative products. Today’s information overload and rapid technological advancement raise needs for effective management of the complexity and heteroge- ity of knowledge, for intelligent and adaptable man–machine interfaces and for pr- ucts and applications that can learn and take decisions by themselves. Although the mystery of human-level intelligence has just started to be uncovered in various int- disciplinary fields, AI is inspired by the respective scientific areas to explore certain theories and models that will provide the methods and techniques to design and - velop human-centered applications that address the above-mentioned needs. This volume contains papers selected for presentation at the 5th Hellenic Conference on Artificial Intelligence (SETN 2008), the official meeting of the Hellenic Society for Artificial Intelligence (EETN). Previous conferences were held at the University of Piraeus (1996), at the Aristotle University of Thessaloniki (2002), at the University of the Aegean (2004) and at
Pindex Conference proceedings 2008
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Emotion in Cognitive Systems Architectureslly inspired, although at very different levels of abstraction. This ranges from explicitly biomimetic approaches, concerned with biological plausibility and scientific modeling, to the use of abstractly biologically inspired techniques such as evolutionary and neural computing in engineering. Howev
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A Multi-agent Environment for Serving Proof Explanations in the Semantic Webws users or agents to issue queries, on a given RDF& rules knowledge base and automatically produces proof explanations for answers produced by a popular programming system (JENA), by interpreting the output from the proof’s trace and converting it into a meaningful representation. It also supports
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A Study of SAT-Based Branching Heuristics for the CSPproblems. Despite their similarities regarding the problem formulation and the basic backtracking search algorithms they use, several advanced techniques have been developed and standardized in one framework but have been rather ignored in the other. One class of such techniques includes branching h
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A Sparse Regression Mixture Model for Clustering Time-Seriesf a smoothing prior over component regression coefficients through a Bayesian framework. This is done by using an appropriate Student-t distribution. The advantages of the sparsity-favouring prior is to make model more robust, less independent on order . of polynomials and improve the clustering pro
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Human Distress Sound Analysis and Characterization Using Advanced Classification Techniqueshis paper presents a system for collecting and analyzing sounds and speech expressions utilizing on-body sensors and advanced classification techniques for emergency events detection. A variety of popular classification and meta-classification algorithms have been evaluated and the corresponding res
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