11,261 research outputs found

    A canonical theory of dynamic decision-making

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    Decision-making behavior is studied in many very different fields, from medicine and eco- nomics to psychology and neuroscience, with major contributions from mathematics and statistics, computer science, AI, and other technical disciplines. However the conceptual- ization of what decision-making is and methods for studying it vary greatly and this has resulted in fragmentation of the field. A theory that can accommodate various perspectives may facilitate interdisciplinary working. We present such a theory in which decision-making is articulated as a set of canonical functions that are sufficiently general to accommodate diverse viewpoints, yet sufficiently precise that they can be instantiated in different ways for specific theoretical or practical purposes. The canons cover the whole decision cycle, from the framing of a decision based on the goals, beliefs, and background knowledge of the decision-maker to the formulation of decision options, establishing preferences over them, and making commitments. Commitments can lead to the initiation of new decisions and any step in the cycle can incorporate reasoning about previous decisions and the rationales for them, and lead to revising or abandoning existing commitments. The theory situates decision-making with respect to other high-level cognitive capabilities like problem solving, planning, and collaborative decision-making. The canonical approach is assessed in three domains: cognitive and neuropsychology, artificial intelligence, and decision engineering

    Autonomic care platform for optimizing query performance

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    Background: As the amount of information in electronic health care systems increases, data operations get more complicated and time-consuming. Intensive Care platforms require a timely processing of data retrievals to guarantee the continuous display of recent data of patients. Physicians and nurses rely on this data for their decision making. Manual optimization of query executions has become difficult to handle due to the increased amount of queries across multiple sources. Hence, a more automated management is necessary to increase the performance of database queries. The autonomic computing paradigm promises an approach in which the system adapts itself and acts as self-managing entity, thereby limiting human interventions and taking actions. Despite the usage of autonomic control loops in network and software systems, this approach has not been applied so far for health information systems. Methods: We extend the COSARA architecture, an infection surveillance and antibiotic management service platform for the Intensive Care Unit (ICU), with self-managed components to increase the performance of data retrievals. We used real-life ICU COSARA queries to analyse slow performance and measure the impact of optimizations. Each day more than 2 million COSARA queries are executed. Three control loops, which monitor the executions and take action, have been proposed: reactive, deliberative and reflective control loops. We focus on improvements of the execution time of microbiology queries directly related to the visual displays of patients' data on the bedside screens. Results: The results show that autonomic control loops are beneficial for the optimizations in the data executions in the ICU. The application of reactive control loop results in a reduction of 8.61% of the average execution time of microbiology results. The combined application of the reactive and deliberative control loop results in an average query time reduction of 10.92% and the combination of reactive, deliberative and reflective control loops provides a reduction of 13.04%. Conclusions: We found that by controlled reduction of queries' executions the performance for the end-user can be improved. The implementation of autonomic control loops in an existing health platform, COSARA, has a positive effect on the timely data visualization for the physician and nurse

    An improved cell controller for the aerospace manufacturing

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    The aerospace manufacturing industry is unique in that production typically focuses on high variety and quality but low volume. Existing flexible manufacturing cells are limited to certain types of machines, robots and cells which makes it difficult to introduce any changes. In this paper idea of treating machines, robots, any hardware and software as resource has been introduced. It describes the development of the Flexa Cell Coordinator (FCC), a system that is providing a solution to manage cells and their resources in a new flexible manner. It can control, organise and coordinate between cells and resources and is capable of controlling remote cells because of its distributed nature. It also provides connectivity with company systems e.g., Enterprise Resource Planner (ERP). It is extendable and capable of adding multiple cells inside the system. In FCC resources (e.g., tracker) can also be shared between cells. The paper presents its development and results of initial successful testing

    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

    Intelligent Energy Optimization for User Intelligible Goals in Smart Home Environments

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    Intelligent management of energy consumption is one of the key issues for future energy distribution systems, smart buildings, and consumer appliances. The problem can be tackled both from the point of view of the utility provider, with the intelligence embedded in the smart grid, or from the point of view of the consumer, thanks to suitable local energy management systems (EMS). Conserving energy, however, should respect the user requirements regarding the desired state of the environment, therefore an EMS should constantly and intelligently find the balance between user requirements and energy saving. The paper proposes a solution to this problem, based on explicit high-level modeling of user intentions and automatic control of device states through the solution and optimization of a constrained Boolean satisfiability problem. The proposed approach has been integrated into a smart environment framework, and promising preliminary results are reporte

    Enhanced cell controller for aerospace manufacturing

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    Aerospace manufacturing industry is unique in that production typically focuses on high variety and quality but extremely low volume. Manufacturing processes are also sometimes unique and not repeatable and, hence, costly. Production is getting more expensive with the introduction of industrial robots and their cells. This paper describes the development of the Flexa Cell Coordinator (FCC), a system that is providing a solution to manage resources at assembly cell level. It can control, organise and coordinate between the resources and is capable of controlling remote cells and resources because of its distributed nature. It also gives insight of a system to the higher management via its rich reporting facility and connectivity with company systems e.g., Enterprise Resource Planner (ERP). It is able to control various kinds of cells and resources (network based) which are not limited to robots and machines. It is extendable and capable of adding multiple numbers of cells inside the system. It also provides the facility of scheduling the task to avoid the deadlocking in the process. In FCC resources (e.g., tracker) can also be shared between cells

    Autonomous Agents for Business Process Management

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    Traditional approaches to managing business processes are often inadequate for large-scale organisation-wide, dynamic settings. However, since Internet and Intranet technologies have become widespread, an increasing number of business processes exhibit these properties. Therefore, a new approach is needed. To this end, we describe the motivation, conceptualization, design, and implementation of a novel agent-based business process management system. The key advance of our system is that responsibility for enacting various components of the business process is delegated to a number of autonomous problem solving agents. To enact their role, these agents typically interact and negotiate with other agents in order to coordinate their actions and to buy in the services they require. This approach leads to a system that is significantly more agile and robust than its traditional counterparts. To help demonstrate these benefits, a companion paper describes the application of our system to a real-world problem faced by British Telecom
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