22 research outputs found

    SIS 2017. Statistics and Data Science: new challenges, new generations

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    The 2017 SIS Conference aims to highlight the crucial role of the Statistics in Data Science. In this new domain of ‘meaning’ extracted from the data, the increasing amount of produced and available data in databases, nowadays, has brought new challenges. That involves different fields of statistics, machine learning, information and computer science, optimization, pattern recognition. These afford together a considerable contribute in the analysis of ‘Big data’, open data, relational and complex data, structured and no-structured. The interest is to collect the contributes which provide from the different domains of Statistics, in the high dimensional data quality validation, sampling extraction, dimensional reduction, pattern selection, data modelling, testing hypotheses and confirming conclusions drawn from the data

    Logic-based Technologies for Multi-agent Systems: A Systematic Literature Review

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    Precisely when the success of artificial intelligence (AI) sub-symbolic techniques makes them be identified with the whole AI by many non-computerscientists and non-technical media, symbolic approaches are getting more and more attention as those that could make AI amenable to human understanding. Given the recurring cycles in the AI history, we expect that a revamp of technologies often tagged as “classical AI” – in particular, logic-based ones will take place in the next few years. On the other hand, agents and multi-agent systems (MAS) have been at the core of the design of intelligent systems since their very beginning, and their long-term connection with logic-based technologies, which characterised their early days, might open new ways to engineer explainable intelligent systems. This is why understanding the current status of logic-based technologies for MAS is nowadays of paramount importance. Accordingly, this paper aims at providing a comprehensive view of those technologies by making them the subject of a systematic literature review (SLR). The resulting technologies are discussed and evaluated from two different perspectives: the MAS and the logic-based ones

    Preclinical MRI of the kidney : methods and protocols

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    This Open Access volume provides readers with an open access protocol collection and wide-ranging recommendations for preclinical renal MRI used in translational research. The chapters in this book are interdisciplinary in nature and bridge the gaps between physics, physiology, and medicine. They are designed to enhance training in renal MRI sciences and improve the reproducibility of renal imaging research. Chapters provide guidance for exploring, using and developing small animal renal MRI in your laboratory as a unique tool for advanced in vivo phenotyping, diagnostic imaging, and research into potential new therapies. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, lists of the necessary materials and reagents, step-by-step, readily reproducible laboratory protocols, and tips on troubleshooting and avoiding known pitfalls. Cutting-edge and thorough, Preclinical MRI of the Kidney: Methods and Protocols is a valuable resource and will be of importance to anyone interested in the preclinical aspect of renal and cardiorenal diseases in the fields of physiology, nephrology, radiology, and cardiology. This publication is based upon work from COST Action PARENCHIMA, supported by European Cooperation in Science and Technology (COST). COST (www.cost.eu) is a funding agency for research and innovation networks. COST Actions help connect research initiatives across Europe and enable scientists to grow their ideas by sharing them with their peers. This boosts their research, career and innovation. PARENCHIMA (renalmri.org) is a community-driven Action in the COST program of the European Union, which unites more than 200 experts in renal MRI from 30 countries with the aim to improve the reproducibility and standardization of renal MRI biomarkers

    Rational Agents: Prioritized Goals, Goal Dynamics, and Agent Programming Languages with Declarative Goals

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    I introduce a specification language for modeling an agent's prioritized goals and their dynamics. I use the situation calculus along with Reiter's solution to the frame problem and predicates for describing agents' knowledge as my base formalism. I further enhance this language by introducing a new sort of infinite paths. Within this language, I discuss how to systematically specify prioritized goals and how to precisely describe the effects of actions on these goals. These actions include adoption and dropping of goals and subgoals. In this framework, an agent's intentions are formally specified as the prioritized intersection of her goals. The ``prioritized'' qualifier above means that the specification must respect the priority ordering of goals when choosing between two incompatible goals. I ensure that the agent's intentions are always consistent with each other and with her knowledge. I investigate two variants with different commitment strategies. Agents specified using the ``optimizing'' agent framework always try to optimize their intentions, while those specified in the ``committed'' agent framework will stick to their intentions even if opportunities to commit to higher priority goals arise when these goals are incompatible with their current intentions. For these, I study properties of prioritized goals and goal change. I also give a definition of subgoals, and prove properties about the goal-subgoal relationship. As an application, I develop a model for a Simple Rational Agent Programming Language (SR-APL) with declarative goals. SR-APL is based on the ``committed agent'' variant of this rich theory, and combines elements from Belief-Desire-Intention (BDI) APLs and the situation calculus based ConGolog APL. Thus SR-APL supports prioritized goals and is grounded on a formal theory of goal change. It ensures that the agent's declarative goals and adopted plans are consistent with each other and with her knowledge. In doing this, I try to bridge the gap between agent theories and practical agent programming languages by providing a model and specification of an idealized BDI agent whose behavior is closer to what a rational agent does. I show that agents programmed in SR-APL satisfy some key rationality requirements

    Refining, Implementing, and Evaluating the Extended Continuous Variable-Specific Resolutions of Feature Interactions

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    Systems that involve feature-oriented software development suffer from feature interactions, in which features affect one another’s behaviour in surprising ways. As the number of features increases, the complexity of examining feature combinations and fixing undesired interactions increases exponentially, such that the workload of resolving interactions comes to dominate feature development. The Feature Interaction Problem results from aiming resolve feature interaction by providing optimal resolutions. Resolution strategies combat the Feature Interaction Problem by offering default strategies that resolve entire classes of interactions, thereby reducing the work of the developer who is charged with the task of resolving interactions. However, most such approaches employ coarse-grained resolution strategies (e.g., feature priority) or a centralized arbitrator. This thesis focuses on evaluating and refining a proposed architecture that resolves features’ conflicting actions on system’s outputs. In this thesis, we extend a proposed architecture based on variable-specific resolution to enable co-resolution of related outputs and to promote smooth continuous resolutions over execution sequences. We implemented our approach within the PreScan simulator for advanced driver assistance systems, and performed a case study involving 15 automotive features that we implemented. We also devised and implemented three resolution strategies for the features’ outputs. The results of the case study show that the approach produces smooth and continuous resolutions of interactions throughout interesting scenarios

    Agent Oriented Software Engineering (AOSE) Approach to Game Development Methodology

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    This thesis investigates existing game development methodologies, through the process of researching game and system development models. The results indicate that these methodologies are engineered to solve specific problems, and most are suitable only for specific game genres. Different approaches to building games have been proposed in recent years. However, most of these methodologies focus on the design and implementation phase. This research aims to enhance game development methodologies by proposing a novel game development methodology, with the ability to function in generic game genres, thereby guiding game developers and designers from the start of the game development phase to the end of the implementation and testing phase. On a positive note, aligning development practice with universal standards makes it far easier to incorporate extra team members at short notice. This increased the confidence when working in the same environment as super developers. In the gaming industry, most game development proceeds directly from game design to the implementation phase, and the researcher observes that this is the only industry in which this occurs. It is a consequence of the game industry’s failure to integrate with modern development techniques. The ultimate aim of this research to apply a new game development methodology using most game elements to enhance success. This development model will align with different game genres, and resolve the gap between industry and research area, so that game developers can focus on the important business of creating games. The primary aim of Agent Oriented Agile Base (AOAB) game development methodology is to present game development techniques in sequential steps to facilitate game creation and close the gap in the existing game development methodologies. Agent technology is used in complex domains such as e-commerce, health, manufacturing, games, etc. In this thesis we are interested in the game domain, which comprises a unique set of characteristics such as automata, collaboration etc. Our AOAB will be based on a predictive approach after adaptation of MaSE methodology, and an adaptive approach using Agile methodology. To ensure proof of concept, AOAB game development methodology will be evaluated against industry principles, providing an industry case study to create a driving test game, which was the problem motivating this research. Furthermore, we conducted two workshops to introduce our methodology to both academic and industry participants. Finally, we prepared an academic experiment to use AOAB in the academic sector. We have analyzed the feedbacks and comments and concluded the strengths and weakness of the AOAB methodology. The research achievements are summarized and proposals for future work outlined

    CACIC 2015 : XXI Congreso Argentino de Ciencias de la Computación. Libro de actas

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    Actas del XXI Congreso Argentino de Ciencias de la Computación (CACIC 2015), realizado en Sede UNNOBA Junín, del 5 al 9 de octubre de 2015.Red de Universidades con Carreras en Informática (RedUNCI

    A Feature Interaction Resolution Scheme Based on Controlled Phenomena

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    Systems that are assembled from independently developed features suffer from feature interactions, in which features affect one another's behaviour in surprising ways. To ensure that a system behaves as intended, developers need to analyze all potential interactions -- and many of the identified interactions need to be fixed and their fixes verified. The feature-interaction problem states that the number of potential interactions to be considered is exponential in the number of features in a system. Resolution strategies combat the feature-interaction problem by offering general strategies that resolve entire classes of interactions, thereby reducing the work of the developer who is charged with the task of resolving interactions. In this thesis, we focus on resolving interactions due to conflict. We present an approach, language, and implementation based on resolver modules modelled in the situation calculus in which the developer can specify an appropriate resolution for each variable under conflict. We performed a case study involving 24 automotive features, and found that the number of resolutions to be specified was much smaller than the number of possible feature interactions (6 resolutions for 24 features), that what constitutes an appropriate resolution strategy is different for different variables, and that the subset of situation calculus we used was sufficient to construct nontrivial resolution strategies for six distinct output variables

    Executable formal specifications of complex distributed systems with CoreASM

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    Formal specifications play a crucial role in the design of reliable complex software systems. Executable formal specifications allow the designer to attain early validation and verification of design using static analysis techniques and accurate simulation of the runtime behavior of the system-to-be. With increasing complexity of software-intensive computer-based systems and the challenges of validation and verification of abstract software models prior to coding, the need for interactive software tools supporting executable formal specifications is even more evident. In this paper, we discuss how CoreASM, an environment for writing and running executable specifications according to the ASM method, provides flexibility and manages the complexity by using an innovative extensible language architecture

    MetTeL: A Generic Tableau Prover.

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