12,262 research outputs found

    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

    An agent-based fuzzy cognitive map approach to the strategic marketing planning for industrial firms

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    This is the post-print version of the final paper published in Industrial Marketing Management. The published article is available from the link below. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. Copyright @ 2013 Elsevier B.V.Industrial marketing planning is a typical example of an unstructured decision making problem due to the large number of variables to consider and the uncertainty imposed on those variables. Although abundant studies identified barriers and facilitators of effective industrial marketing planning in practice, the literature still lacks practical tools and methods that marketing managers can use for the task. This paper applies fuzzy cognitive maps (FCM) to industrial marketing planning. In particular, agent based inference method is proposed to overcome dynamic relationships, time lags, and reusability issues of FCM evaluation. MACOM simulator also is developed to help marketing managers conduct what-if scenarios to see the impacts of possible changes on the variables defined in an FCM that represents industrial marketing planning problem. The simulator is applied to an industrial marketing planning problem for a global software service company in South Korea. This study has practical implication as it supports marketing managers for industrial marketing planning that has large number of variables and their cause–effect relationships. It also contributes to FCM theory by providing an agent based method for the inference of FCM. Finally, MACOM also provides academics in the industrial marketing management discipline with a tool for developing and pre-verifying a conceptual model based on qualitative knowledge of marketing practitioners.Ministry of Education, Science and Technology (Korea

    Methodologies for self-organising systems:a SPEM approach

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    We define ’SPEM fragments’ of five methods for developing self-organising multi-agent systems. Self-organising traffic lights controllers provide an application scenario

    Aspect-oriented interaction in multi-organisational web-based systems

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    Separation of concerns has been presented as a promising tool to tackle the design of complex systems in which cross-cutting properties that do not fit into the scope of a class must be satisfied. Unfortunately, current proposals assume that objects interact by means of object-oriented method calls, which implies that they embed interactions with others into their functional code. This makes them dependent on this interaction model, and makes it difficult to reuse them in a context in which another interaction model is more suited, e.g., tuple spaces, multiparty meetings, ports, and so forth. In this paper, we show that functionality can be described separately from the interaction model used, which helps enhance reusability of functional code and coordination patterns. Our proposal is innovative in that it is the first that achieves a clear separation between functionality and interaction in an aspect-oriented manner. In order to show that it is feasible, we adapted the multiparty interaction model to the context of multiorganisational web-based systems and developed a class framework to build business objects whose performance rates comparably to handmade implementations; the development time, however, decreases significantly.Comisión Interministerial de Ciencia y Tecnología TIC2000-1106-C02-0

    Separating Agent-Functioning and Inter-Agent Coordination by Activated Modules: The DECOMAS Architecture

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    The embedding of self-organizing inter-agent processes in distributed software applications enables the decentralized coordination system elements, solely based on concerted, localized interactions. The separation and encapsulation of the activities that are conceptually related to the coordination, is a crucial concern for systematic development practices in order to prepare the reuse and systematic integration of coordination processes in software systems. Here, we discuss a programming model that is based on the externalization of processes prescriptions and their embedding in Multi-Agent Systems (MAS). One fundamental design concern for a corresponding execution middleware is the minimal-invasive augmentation of the activities that affect coordination. This design challenge is approached by the activation of agent modules. Modules are converted to software elements that reason about and modify their host agent. We discuss and formalize this extension within the context of a generic coordination architecture and exemplify the proposed programming model with the decentralized management of (web) service infrastructures

    A Framework for Design and Composition of Semantic Web Services

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    Semantic Web Services (SWS) are Web Services (WS) whose description is semantically enhanced with markup languages (e.g., OWL-S). This semantic description will enable external agents and programs to discover, compose and invoke SWSs. However, as a previous step to the specification of SWSs in a language, it must be designed at a conceptual level to guarantee its correctness and avoid inconsistencies among its internal components. In this paper, we present a framework for design and (semi) automatic composition of SWSs at a language-independent and knowledge level. This framework is based on a stack of ontologies that (1) describe the different parts of a SWS; and (2) contain a set of axioms that are really design rules to be verified by the ontology instances. Based on these ontologies, design and composition of SWSs can be viewed as the correct instantiation of the ontologies themselves. Once these instances have been created they will be exported to SWS languages such as OWL-S

    Systematically Engineering Self-Organizing Systems: The SodekoVS Approach

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    Self-organizing systems promise new software quality attributes that are very hard to obtain using standard software engineering approaches. In accordance with the visions of e.g. autonomic computing and organic computing, self-organizing systems promote self-adaptability as one major property helping to realize software that can manage itself at runtime. In this respect, self-adaptability can be seen as a necessary foundation for realizing e.g. self* properties such as self-configuration or self-protection. However, the systematic development of systems exhibiting such properties challenges current development practices. The SodekoVS project addresses the challenge to purposefully engineer adaptivity by proposing a new approach that considers the system architecture as well as the software development methodology as integral intertwined aspects for system construction. Following the proposed process, self-organizing dynamics, inspired by biological, physical and social systems, can be integrated into applications by composing modules that distribute feedback control structures among system entities. These compositions support hierarchical as well as completely decentralized solutions without a single point of failure. This novel development conception is supported by a reference architecture, a tailored programming model as well as a library of ready to use self-organizing patterns. The key challenges, recent research activities, application scenarios as well as intermediate results are discussed
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