8 research outputs found

    A machine-machine collaboration formalism based on web services for groupware tailorability

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    International audienceIn this paper, we propose a machine-machine collaboration formalism to support groupware tailorability. Our work is based on the 3C functional model by Ellis that decomposes collaboration between users into communication, coordination and cooperation phases. Through our research, we realized that Web services are powerful distributed components offering the desired tools in order to adapt a groupware system to the real needs of users. Therefore, we use this technology to define a collaboration protocol between machines over the network for implementing tailorability in CSCW systems. A groupware architecture is presented based on the proposed formalism. We argue that a protocol between machines over the internet should be defined in order to exchange common services in real time collaboration

    Industrial agents in the era of service-oriented architectures and cloudbased industrial infrastructures

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    The umbrella paradigm underpinning novel collaborative industrial systems is to consider the set of intelligent system units as a conglomerate of distributed, autonomous, intelligent, proactive, fault-tolerant, and reusable units, which operate as a set of cooperating entities (Colombo and Karnouskos, 2009). These entities are forming an evolvable infrastructure, entering and/or going out (plug-in/plugout) in an asynchronous manner. Moreover, these entities, having each of them their own functionalities, data, and associated information are now connected and able to interact. They are capable of working in a proactive manner, initiating collaborative actions and dynamically interacting with each other in order to achieve both local and global objectives.info:eu-repo/semantics/publishedVersio

    Using software abstraction to develop an agent based system.

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    The main contribution of the thesis is to present a systematic process to develop an agent-based system that assists a system developer to construct the required system, through a series of modelling activities, employing several levels of abstraction to show the milestones and produce intermediate deliverables. Current practice emphasises "downstream activities" such as implementation at the expense of "upstream activities" such as "modelling". The research has found that the development process for an agent system consists of three phases: agent system development, agent environment development and agent system deployment. The first and second phases represent an intertwined spiral model. All three phases themselves consist of three stages. Each phase employs different development techniques and each stage uses appropriate models and tools such as problem domain model, agent use cases, scenarios, agent system architecture, plan model and individual agent model.The proposed agent development method is applied to two case studies: a Filtering Agent System and Diabetic Consultation System. Both systems have been implemented and tested. Three distinct ways were used to evaluate the proposed method. First, comparing with the criteria of a methodology. Second, comparing it with the current agent-oriented methodologies. Third, informal observations from a potential user community.In conclusion, the research has demonstrated an effective synthesising process to build a set of agent concepts, development life-cycle and modelling to show a systematic process for developing agent systems. Moreover, by employing a whole host of software abstraction tools and techniques in the process, two benefits accrue: the introduction of more 'up stream' activities as well as placing modelling at the heart of the process. Illustratively, we could say that the modelling presented here does for agent systems what data flow diagram and data entity diagram have done for structured methodologies, i.e. raise the level of abstraction employed

    Combining SOA and BPM Technologies for Cross-System Process Automation

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    This paper summarizes the results of an industry case study that introduced a cross-system business process automation solution based on a combination of SOA and BPM standard technologies (i.e., BPMN, BPEL, WSDL). Besides discussing major weaknesses of the existing, custom-built, solution and comparing them against experiences with the developed prototype, the paper presents a course of action for transforming the current solution into the proposed solution. This includes a general approach, consisting of four distinct steps, as well as specific action items that are to be performed for every step. The discussion also covers language and tool support and challenges arising from the transformation

    Technological roadmap on AI planning and scheduling

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    At the beginning of the new century, Information Technologies had become basic and indispensable constituents of the production and preparation processes for all kinds of goods and services and with that are largely influencing both the working and private life of nearly every citizen. This development will continue and even further grow with the continually increasing use of the Internet in production, business, science, education, and everyday societal and private undertaking. Recent years have shown, however, that a dramatic enhancement of software capabilities is required, when aiming to continuously provide advanced and competitive products and services in all these fast developing sectors. It includes the development of intelligent systems – systems that are more autonomous, flexible, and robust than today’s conventional software. Intelligent Planning and Scheduling is a key enabling technology for intelligent systems. It has been developed and matured over the last three decades and has successfully been employed for a variety of applications in commerce, industry, education, medicine, public transport, defense, and government. This document reviews the state-of-the-art in key application and technical areas of Intelligent Planning and Scheduling. It identifies the most important research, development, and technology transfer efforts required in the coming 3 to 10 years and shows the way forward to meet these challenges in the short-, medium- and longer-term future. The roadmap has been developed under the regime of PLANET – the European Network of Excellence in AI Planning. This network, established by the European Commission in 1998, is the co-ordinating framework for research, development, and technology transfer in the field of Intelligent Planning and Scheduling in Europe. A large number of people have contributed to this document including the members of PLANET non- European international experts, and a number of independent expert peer reviewers. All of them are acknowledged in a separate section of this document. Intelligent Planning and Scheduling is a far-reaching technology. Accepting the challenges and progressing along the directions pointed out in this roadmap will enable a new generation of intelligent application systems in a wide variety of industrial, commercial, public, and private sectors

    Combining FIPA Agents and Web Services for the Design of Tailorable Groupware Architecture

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    International audienceIn this paper, we present a new groupware architectural model called UD3, which is based on the integration of web services technologies with software agents. The aim is to design a tailorable groupware architecture using the integration of both technologies, thus using properties of each while reinforcing their individual strengths. In fact, agent-oriented technology is claimed to become the next breakthrough in the development and implementation of large-scale complex systems, while Web services are fast emerging technologies for connecting remotely executing programs via well established internet protocols. Web services and agents were originally developed with different standards, thus their integration becomes important in the context of groupware tailorability, giving a totally innovative approach for designing collaborative applications

    Web Usage Mining: Algorithms and results

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