8,286 research outputs found

    On Formal Methods for Collective Adaptive System Engineering. {Scalable Approximated, Spatial} Analysis Techniques. Extended Abstract

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    In this extended abstract a view on the role of Formal Methods in System Engineering is briefly presented. Then two examples of useful analysis techniques based on solid mathematical theories are discussed as well as the software tools which have been built for supporting such techniques. The first technique is Scalable Approximated Population DTMC Model-checking. The second one is Spatial Model-checking for Closure Spaces. Both techniques have been developed in the context of the EU funded project QUANTICOL.Comment: In Proceedings FORECAST 2016, arXiv:1607.0200

    A Pattern based Modelling for Self-Organizing Multi-Agent Systems with Event-B

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    International audienceSelf-Organizing Multi-Agent Systems (SO-MAS) are defined as a set of autonomous entities called agents interacting together in order to achieve a given task. Generally, the development process of these systems is based on the bottom-up approach which focuses on the design of the entities individual behavior. The main question arising when developing SO-MAS is how to insure that the designed entities, when interacting together, will give rise to the desired behavior? Our proposition to deal with this question is to use formal methods. We propose a correct by construction method for systematic design of SO-MAS based on the use of design patterns and formal stepwise refinements. Our work gives guidelines to assist the designer when developing the individual behavior of the entities and prove its correctness at the early stages of the design process. The method is illustrated with the foraging ants’ case study

    Towards adaptive multi-robot systems: self-organization and self-adaptation

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    Dieser Beitrag ist mit Zustimmung des Rechteinhabers aufgrund einer (DFG geförderten) Allianz- bzw. Nationallizenz frei zugänglich.This publication is with permission of the rights owner freely accessible due to an Alliance licence and a national licence (funded by the DFG, German Research Foundation) respectively.The development of complex systems ensembles that operate in uncertain environments is a major challenge. The reason for this is that system designers are not able to fully specify the system during specification and development and before it is being deployed. Natural swarm systems enjoy similar characteristics, yet, being self-adaptive and being able to self-organize, these systems show beneficial emergent behaviour. Similar concepts can be extremely helpful for artificial systems, especially when it comes to multi-robot scenarios, which require such solution in order to be applicable to highly uncertain real world application. In this article, we present a comprehensive overview over state-of-the-art solutions in emergent systems, self-organization, self-adaptation, and robotics. We discuss these approaches in the light of a framework for multi-robot systems and identify similarities, differences missing links and open gaps that have to be addressed in order to make this framework possible

    GA-optimization for rapid prototype system demonstration

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    An application of the Genetic Algorithm (GA) is discussed. A novel scheme of Hierarchical GA was developed to solve complicated engineering problems which require optimization of a large number of parameters with high precision. High level GAs search for few parameters which are much more sensitive to the system performance. Low level GAs search in more detail and employ a greater number of parameters for further optimization. Therefore, the complexity of the search is decreased and the computing resources are used more efficiently

    10 - Self-Organisation & MAS

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