7,504 research outputs found

    An agent-based architecture for managing the provision of community care - the INCA (Intelligent Community Alarm) experience

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    Community Care is an area that requires extensive cooperation between independent agencies, each of which needs to meet its own objectives and targets. None are engaged solely in the delivery of community care, and need to integrate the service with their other responsibilities in a coherent and efficient manner. Agent technology provides the means by which effective cooperation can take place without compromising the essential security of both the client and the agencies involved as the appropriate set of responses can be generated through negotiation between the parties without the need for access to the main information repositories that would be necessary with conventional collaboration models. The autonomous nature of agents also means that a variety of agents can cooperate together with various local capabilities, so long as they conform to the relevant messaging requirements. This allows a variety of agents, with capabilities tailored to the carers to which they are attached to be developed so that cost-effective solutions can be provided. </p

    Bi-directional Ontology Versioning BOV

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    his paper defines a new type of ontology versioning: Bi-directional Ontology Versioning: BOV. BOV provides bi-directional mappings and transformations between concepts in two ontology versions. BOV is identified by two levels mapping processes: linguistic mapping and structural mapping. BOV can satisfy the requirement of mapping in distributed environment

    A Real-Time Unsupervised Neural Network for the Low-Level Control of a Mobile Robot in a Nonstationary Environment

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    This article introduces a real-time, unsupervised neural network that learns to control a two-degree-of-freedom mobile robot in a nonstationary environment. The neural controller, which is termed neural NETwork MObile Robot Controller (NETMORC), combines associative learning and Vector Associative Map (YAM) learning to generate transformations between spatial and velocity coordinates. As a result, the controller learns the wheel velocities required to reach a target at an arbitrary distance and angle. The transformations are learned during an unsupervised training phase, during which the robot moves as a result of randomly selected wheel velocities. The robot learns the relationship between these velocities and the resulting incremental movements. Aside form being able to reach stationary or moving targets, the NETMORC structure also enables the robot to perform successfully in spite of disturbances in the enviroment, such as wheel slippage, or changes in the robot's plant, including changes in wheel radius, changes in inter-wheel distance, or changes in the internal time step of the system. Finally, the controller is extended to include a module that learns an internal odometric transformation, allowing the robot to reach targets when visual input is sporadic or unreliable.Sloan Fellowship (BR-3122), Air Force Office of Scientific Research (F49620-92-J-0499

    Design reuse research : a computational perspective

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    This paper gives an overview of some computer based systems that focus on supporting engineering design reuse. Design reuse is considered here to reflect the utilisation of any knowledge gained from a design activity and not just past designs of artefacts. A design reuse process model, containing three main processes and six knowledge components, is used as a basis to identify the main areas of contribution from the systems. From this it can be concluded that while reuse libraries and design by reuse has received most attention, design for reuse, domain exploration and five of the other knowledge components lack research effort

    KSNet-Approach to Knowledge Fusion from Distributed Sources

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    The rapidity of the decision making process is an important factor in different branches of the human life (business, healthcare, industry, military applications etc.). Since responsible persons make decisions using available knowledge, it is important for knowledge management systems to deliver necessary and timely information. Knowledge logistics is a new direction in the knowledge management addressing this. Technology of knowledge fusion, based on the synergistic use of knowledge from multiple distributed sources, is a basis for these activities. The paper presents an overview of a Knowledge Source Network configuration approach (KSNet-approach) to knowledge fusion, multi-agent architecture and research prototype of the KSNet knowledge fusion system based on this approach

    An Ontology Based Approach To The Integration Of Heterogeneous Information Systems Supporting Integrated Provincial Administration In Khon Kaen, Thailand

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    Information systems are a necessity to the administration of organizations. In a recent reform to the Thai administration, the governor of each province is entrusted with the full responsibility for the strategic planning and execution of the Integrated Provincial Administration (IPA). This presents a big challenge and many difficult problems for a potentially fast growing, both economically and demographically, province, such as Khon Kaen. To provide the administrator of the province with reliable and up to date information, the Provincial Operation Centre (POC) has been set up and assigned the task of collecting all required information from disparate information systems, many of which are legacy systems. This information lacks interoperability and integration of data due to many different structures and semantic heterogeneity encountered in many information systems. This research is a part of a collaborative data sources community development project. It attempts to aid high-level decision makers by using ontology to resolve heterogeneities among many disparate data sources. After relevant data sources are identified, they are analysed to reveal important and corresponding concepts, attributes and relations. They are then used in the creation of ontologies to resolve schematic and semantic conflicts in the data sources. The integration of many heterogeneous information systems will provide a unified view of information facilitating the provincial administrator in his decision making

    A neuro-fuzzy architecture for real-time applications

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    Neural networks and fuzzy expert systems perform the same task of functional mapping using entirely different approaches. Each approach has certain unique features. The ability to learn specific input-output mappings from large input/output data possibly corrupted by noise and the ability to adapt or continue learning are some important features of neural networks. Fuzzy expert systems are known for their ability to deal with fuzzy information and incomplete/imprecise data in a structured, logical way. Since both of these techniques implement the same task (that of functional mapping--we regard 'inferencing' as one specific category under this class), a fusion of the two concepts that retains their unique features while overcoming their individual drawbacks will have excellent applications in the real world. In this paper, we arrive at a new architecture by fusing the two concepts. The architecture has the trainability/adaptibility (based on input/output observations) property of the neural networks and the architectural features that are unique to fuzzy expert systems. It also does not require specific information such as fuzzy rules, defuzzification procedure used, etc., though any such information can be integrated into the architecture. We show that this architecture can provide better performance than is possible from a single two or three layer feedforward neural network. Further, we show that this new architecture can be used as an efficient vehicle for hardware implementation of complex fuzzy expert systems for real-time applications. A numerical example is provided to show the potential of this approach

    An agent-based architecture for managing the provision of community care: the INCA (Intelligent Community Alarm) experience

    Get PDF
    Community care is an area that requires extensive ooperation between independent agencies, each of which needs to meet its own objectives and targets. None are engaged solely in the delivery of community care, and need to integrate the service with their other responsibilities in a coherent and efficient manner. Agent technology provides the means by which effective cooperation can take place without compromising the essential security of both the client and the agencies involved as the appropriate set of responses can be generated through negotiation between the parties without the need for access to the main information repositories that would be necessary with conventional collaboration models. The autonomous nature of agents also means that a variety of agents can cooperate together with various local capabilities, so long as they conform to the relevant messaging requirements. This allows a variety of agents, with capabilities tailored to the carers to which they are attached to be developed so that cost-effective solutions can be provided
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