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            <title xml:lang="en">Investigating Fluid-Flow Semantics of Asynchronous Tuple-Based Process Languages for Collective Adaptive Systems</title>
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            <idno type="halRefHtml">&lt;i&gt;17th International Conference on Coordination Languages and Models (COORDINATION)&lt;/i&gt;, Jun 2015, Grenoble, France. pp.19-34, &lt;a target="_blank" href="https://dx.doi.org/10.1007/978-3-319-19282-6_2"&gt;&amp;#x27E8;10.1007/978-3-319-19282-6_2&amp;#x27E9;&lt;/a&gt;</idno>
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                <title xml:lang="en">Investigating Fluid-Flow Semantics of Asynchronous Tuple-Based Process Languages for Collective Adaptive Systems</title>
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                    <forename type="first">Diego</forename>
                    <surname>Latella</surname>
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                  <title>17th International Conference on Coordination Languages and Models (COORDINATION)</title>
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                  <date type="end">2015-06-04</date>
                  <settlement>Grenoble</settlement>
                  <country key="FR">France</country>
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                <editor>Tom Holvoet</editor>
                <editor>Mirko Viroli</editor>
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                <term xml:lang="en">Continuous time markov chains</term>
                <term xml:lang="en">Fluid-flow approximation</term>
                <term xml:lang="en">Stochastic process algebras</term>
                <term xml:lang="en">Asynchronous coordination languages</term>
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              <p>Recently, there has been growing interest in nature-inspired interaction paradigms for Collective Adaptive Systems, for modelling and implementation of adaptive and context-aware coordination, among which the promising pheromone-based interaction paradigm. System modelling in the context of such a paradigm may be facilitated by the use of languages in which adaptive interaction is decoupled in time and space through asynchronous buffered communication, e.g. asynchronous, repository- or tuple-based languages. In this paper we propose a differential semantics for such languages. In particular, we consider an asynchronous, repository based modelling kernel-language which is a restricted version of LINDA, extended with stochastic information about action duration. We provide stochastic formal semantics for both an agent-based view and a population-based view. We then derive an ordinary differential equation semantics from the latter, which provides a fluid-flow deterministic approximation for the mean behaviour of large populations. We show the application of the language and the ODE analysis on a benchmark example of foraging ants.</p>
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