2,008 research outputs found

    An Approach to Agent-Based Service Composition and Its Application to Mobile

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    This paper describes an architecture model for multiagent systems that was developed in the European project LEAP (Lightweight Extensible Agent Platform). Its main feature is a set of generic services that are implemented independently of the agents and can be installed into the agents by the application developer in a flexible way. Moreover, two applications using this architecture model are described that were also developed within the LEAP project. The application domain is the support of mobile, virtual teams for the German automobile club ADAC and for British Telecommunications

    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

    Resilience, reliability, and coordination in autonomous multi-agent systems

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    Acknowledgements The research reported in this paper was funded and supported by various grants over the years: Robotics and AI in Nuclear (RAIN) Hub (EP/R026084/1); Future AI and Robotics for Space (FAIR-SPACE) Hub (EP/R026092/1); Offshore Robotics for Certification of Assets (ORCA) Hub (EP/R026173/1); the Royal Academy of Engineering under the Chair in Emerging Technologies scheme; Trustworthy Autonomous Systems “Verifiability Node” (EP/V026801); Scrutable Autonomous Systems (EP/J012084/1); Supporting Security Policy with Effective Digital Intervention (EP/P011829/1); The International Technology Alliance in Network and Information Sciences.Peer reviewedPostprin

    Practical applications of multi-agent systems in electric power systems

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    The transformation of energy networks from passive to active systems requires the embedding of intelligence within the network. One suitable approach to integrating distributed intelligent systems is multi-agent systems technology, where components of functionality run as autonomous agents capable of interaction through messaging. This provides loose coupling between components that can benefit the complex systems envisioned for the smart grid. This paper reviews the key milestones of demonstrated agent systems in the power industry and considers which aspects of agent design must still be addressed for widespread application of agent technology to occur

    OperA/ALIVE/OperettA

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    Comprehensive models for organizations must, on the one hand, be able to specify global goals and requirements but, on the other hand, cannot assume that particular actors will always act according to the needs and expectations of the system design. Concepts as organizational rules (Zambonelli 2002), norms and institutions (Dignum and Dignum 2001; Esteva et al. 2002), and social structures (Parunak and Odell 2002) arise from the idea that the effective engineering of organizations needs high-level, actor-independent concepts and abstractions that explicitly define the organization in which agents live (Zambonelli 2002).Peer ReviewedPostprint (author's final draft

    Negotiating agents that learn about others’ preferences

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    In multiagent systems, an agent does not usually have complete information about the preferences and decision making processes of other agents. This might prevent the agents from making coordinated choices, purely due to their ignorance of what others want. This paper describes the integration of a learning module into a communication-intensive negotiating agent architecture. The learning module gives the agents the ability to learn about other agents&rsquo; preferences via past interactions. Over time, the agents can incrementally update their models of other agents&rsquo; preferences and use them to make better coordinated decisions. Combining both communication and learning, as two complement knowledge acquisition methods, helps to reduce the amount of communication needed on average, and is justified in situation where communication is computationally costly or simply not desirable (e.g. to preserve the individual privacy).<br /
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