116,800 research outputs found

    Discovery Is Never By Chance: Designing for (Un)Serendipity

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    Serendipity has a long tradition in the history of science as having played a key role in many significant discoveries. Computer scientists, valuing the role of serendipity in discovery, have attempted to design systems that encourage serendipity. However, that research has focused primarily on only one aspect of serendipity: that of chance encounters. In reality, for serendipity to be valuable chance encounters must be synthesized into insight. In this paper we show, through a formal consideration of serendipity and analysis of how various systems have seized on attributes of interpreting serendipity, that there is a richer space for design to support serendipitous creativity, innovation and discovery than has been tapped to date. We discuss how ideas might be encoded to be shared or discovered by ‘association-hunting’ agents. We propose considering not only the inventor’s role in perceiving serendipity, but also how that inventor’s perception may be enhanced to increase the opportunity for serendipity. We explore the role of environment and how we can better enable serendipitous discoveries to find a home more readily and immediately

    A Process-Oriented Architecture for Complex System Modelling

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    A fine-grained massively-parallel process-oriented model of platelets (potentially artificial) within a blood vessel is presented. This is a CSP inspired design, expressed and implemented using the occam-pi language. It is part of the TUNA pilot study on nanite assemblers at the universities of York, Surrey and Kent. The aim for this model is to engineer emergent behaviour from the platelets, such that they respond to a wound in the blood vessel wall in a way similar to that found in the human body -- i.e. the formation of clots to stem blood flow from the wound and facilitate healing. An architecture for a three dimensional model (relying strongly on the dynamic and mobile capabilities of occam-pi) is given, along with mechanisms for visualisation and interaction. The biological accuracy of the current model is very approximate. However, its process-oriented nature enables simple refinement (through the addition of processes modelling different stimulants/inhibitors of the clotting reaction, different platelet types and other participating organelles) to greater and greater realism. Even with the current system, simple experiments are possible and have scientific interest (e.g. the effect of platelet density on the success of the clotting mechanism in stemming blood flow: too high or too low and the process fails). General principles for the design of large and complex system models are drawn. The described case study runs to millions of processes engaged in ever-changing communication topologies. It is free from deadlock, livelock, race hazards and starvation em by design, employing a small set of synchronisation patterns for which we have proven safety theorems

    A Model-Driven Engineering Approach for ROS using Ontological Semantics

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    This paper presents a novel ontology-driven software engineering approach for the development of industrial robotics control software. It introduces the ReApp architecture that synthesizes model-driven engineering with semantic technologies to facilitate the development and reuse of ROS-based components and applications. In ReApp, we show how different ontological classification systems for hardware, software, and capabilities help developers in discovering suitable software components for their tasks and in applying them correctly. The proposed model-driven tooling enables developers to work at higher abstraction levels and fosters automatic code generation. It is underpinned by ontologies to minimize discontinuities in the development workflow, with an integrated development environment presenting a seamless interface to the user. First results show the viability and synergy of the selected approach when searching for or developing software with reuse in mind.Comment: Presented at DSLRob 2015 (arXiv:1601.00877), Stefan Zander, Georg Heppner, Georg Neugschwandtner, Ramez Awad, Marc Essinger and Nadia Ahmed: A Model-Driven Engineering Approach for ROS using Ontological Semantic

    The underlying social dynamics of paradigm shifts

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    We develop here a multi-agent model of the creation of knowledge (scientific progress or technological evolution) within a community of researchers devoted to such endeavors. In the proposed model, agents learn in a physical-technological landscape, and weight is attached to both individual search and social influence. We find that the combination of these two forces together with random experimentation can account for both i) marginal change, that is, periods of normal science or refinements on the performance of a given technology (and in which the community stays in the neighborhood of the current paradigm); and ii) radical change, which takes the form of scientific paradigm shifts (or discontinuities in the structure of performance of a technology) that is observed as a swift migration of the knowledge community towards the new and superior paradigm. The efficiency of the search process is heavily dependent on the weight that agents posit on social influence. The occurrence of a paradigm shift becomes more likely when each member of the community attaches a small but positive weight to the experience of his/her peers. For this parameter region, nevertheless, a conservative force is exerted by the representatives of the current paradigm. However, social influence is not strong enough to seriously hamper individual discovery, and can act so as to empower successful individual pioneers who have conquered the new and superior paradigm.Fil: Rodriguez Sickert, Carlos. Universidad del Desarrollo; ChileFil: Cosmelli, Diego. Pontificia Universidad Católica de Chile; ChileFil: Claro, Francisco. Pontificia Universidad Católica de Chile; ChileFil: Fuentes, Miguel Angel. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad San Sebastián; Chil

    Modular organisation of interaction networks based on asymptotic dynamics

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    This paper investigates questions related to the modularity in discrete models of biological interaction networks. We develop a theoretical framework based on the analysis of their asymptotic dynamics. More precisely, we exhibit formal conditions under which agents of interaction networks can be grouped into modules. As a main result, we show that the usual decomposition in strongly connected components fulfils the conditions of being a modular organisation. Furthermore, we point out that our framework enables a finer analysis providing a decomposition in elementary modules
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