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.

Investigating Fluid-Flow Semantics of Asynchronous Tuple-Based Process Languages for Collective Adaptive Systems

Loreti Michele;
2015

Abstract

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.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11581/405049
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