73,798 research outputs found

    Applications of agent architectures to decision support in distributed simulation and training systems

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    This work develops the approach and presents the results of a new model for applying intelligent agents to complex distributed interactive simulation for command and control. In the framework of tactical command, control communications, computers and intelligence (C4I), software agents provide a novel approach for efficient decision support and distributed interactive mission training. An agent-based architecture for decision support is designed, implemented and is applied in a distributed interactive simulation to significantly enhance the command and control training during simulated exercises. The architecture is based on monitoring, evaluation, and advice agents, which cooperate to provide alternatives to the dec ision-maker in a time and resource constrained environment. The architecture is implemented and tested within the context of an AWACS Weapons Director trainer tool. The foundation of the work required a wide range of preliminary research topics to be covered, including real-time systems, resource allocation, agent-based computing, decision support systems, and distributed interactive simulations. The major contribution of our work is the construction of a multi-agent architecture and its application to an operational decision support system for command and control interactive simulation. The architectural design for the multi-agent system was drafted in the first stage of the work. In the next stage rules of engagement, objective and cost functions were determined in the AWACS (Airforce command and control) decision support domain. Finally, the multi-agent architecture was implemented and evaluated inside a distributed interactive simulation test-bed for AWACS Vv\u27Ds. The evaluation process combined individual and team use of the decision support system to improve the performance results of WD trainees. The decision support system is designed and implemented a distributed architecture for performance-oriented management of software agents. The approach provides new agent interaction protocols and utilizes agent performance monitoring and remote synchronization mechanisms. This multi-agent architecture enables direct and indirect agent communication as well as dynamic hierarchical agent coordination. Inter-agent communications use predefined interfaces, protocols, and open channels with specified ontology and semantics. Services can be requested and responses with results received over such communication modes. Both traditional (functional) parameters and nonfunctional (e.g. QoS, deadline, etc.) requirements and captured in service requests

    Survey of dynamic scheduling in manufacturing systems

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    A Semantic Grid Oriented to E-Tourism

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    With increasing complexity of tourism business models and tasks, there is a clear need of the next generation e-Tourism infrastructure to support flexible automation, integration, computation, storage, and collaboration. Currently several enabling technologies such as semantic Web, Web service, agent and grid computing have been applied in the different e-Tourism applications, however there is no a unified framework to be able to integrate all of them. So this paper presents a promising e-Tourism framework based on emerging semantic grid, in which a number of key design issues are discussed including architecture, ontologies structure, semantic reconciliation, service and resource discovery, role based authorization and intelligent agent. The paper finally provides the implementation of the framework.Comment: 12 PAGES, 7 Figure

    Product Specification: Distributed Control Module (DOE-PSU-0000922-5)

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    This product specification describes the architecture, implementation, and hardware descriptions of a Distributed Control Module (DCM) prototype. A DCM is an enabling technology for distributed energy resources (DER). DERs are grid-enabled generation, storage, and load devices that are owned by utility customers. DCMs enable information exchange between a distributed energy resource management system (DERMS) and DERs for the purpose of networking large numbers of DERs. The DCM prototype described within this document enables DER participation in a service-oriented aggregation system. A DERMS server provides IEEE 2030.5 smart energy resource services to DCM clients using a request/response information exchange process. DCMs serve as gateways between the DERMS and the DERs, and they act as agents on behalf of the DER owners to provide intelligent management of the DERs

    Towards a Framework for Developing Mobile Agents for Managing Distributed Information Resources

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    Distributed information management tools allow users to author, disseminate, discover and manage information within large-scale networked environments, such as the Internet. Agent technology provides the flexibility and scalability necessary to develop such distributed information management applications. We present a layered organisation that is shared by the specific applications that we build. Within this organisation we describe an architecture where mobile agents can move across distributed environments, integrate with local resources and other mobile agents, and communicate their results back to the user

    Morphological Computation as Natural Ecosystem Service for Intelligent Technology

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    The basic idea of natural computing is learning from nature. The naturalist framework provides an info-computational architecture for cognizing agents, modeling living organisms as informational structures with computational dynamics. Intrinsic natural information processes can be used asnatural ecosystem services to perform resource-efficient computation, instead of explicitly controlling every step of the computational process. In robotics, morphological computing is using inherent material properties to produce behavior like passive walking or grasping. In general, morphology (structure, shape, form, material) is self-organizing into dynamic structures resulting in growth, development, and decision-making that represent processes of embodied cognition and constitute the naturalized basis of intelligent behavior

    Constructing a Virtual Training Laboratory Using Intelligent Agents

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    This paper reports on the results and experiences of the Trilogy project; a collaborative project concerned with the development of a virtual research laboratory using intelligence agents. This laboratory is designed to support the training of research students in telecommunications traffic engineering. Training research students involves a number of basic activities. They may seek guidance from, or exchange ideas with, more experienced colleagues. High quality academic papers, books and research reports provide a sound basis for developing and maintaining a good understanding of an area of research. Experimental tools enable new ideas to be evaluated, and hypotheses tested. These three components-collaboration, information and experimentation- are central to any research activity, and a good training environment for research should integrate them in a seamless fashion. To this end, we describe the design and implementation of an agent-based virtual laboratory

    Part 1: a process view of nature. Multifunctional integration and the role of the construction agent

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    This is the first of two linked articles which draw s on emerging understanding in the field of biology and seeks to communicate it to those of construction, engineering and design. Its insight is that nature 'works' at the process level, where neither function nor form are distinctions, and materialisation is both the act of negotiating limited resource and encoding matter as 'memory', to sustain and integrate processes through time. It explores how biological agents derive work by creating 'interfaces' between adjacent locations as membranes, through feedback. Through the tension between simultaneous aggregation and disaggregation of matter by agents with opposing objectives, many functions are integrated into an interface as it unfolds. Significantly, biological agents induce flow and counterflow conditions within biological interfaces, by inducing phase transition responses in the matte r or energy passing through them, driving steep gradients from weak potentials (i.e. shorter distances and larger surfaces). As with biological agents, computing, programming and, increasingly digital sensor and effector technologies share the same 'agency' and are thus convergent
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