187 resultados para software agents


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PEGS (Production and Environmental Generic Scheduler) is a generic production scheduler that produces good schedules over a wide range of problems. It is centralised, using search strategies with the Shifting Bottleneck algorithm. We have also developed an alternative distributed approach using software agents. In some cases this reduces run times by a factor of 10 or more. In most cases, the agent-based program also produces good solutions for published benchmark data, and the short run times make our program useful for a large range of problems. Test results show that the agents can produce schedules comparable to the best found so far for some benchmark datasets and actually better schedules than PEGS on our own random datasets. The flexibility that agents can provide for today's dynamic scheduling is also appealing. We suggest that in this sort of generic or commercial system, the agent-based approach is a good alternative.

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We present a novel Service Level Agreement (SLA)-driven service provisioning architecture, which enables dynamic and flexible bandwidth reservation schemes on a per-user or per-application basis. Various session level SLA negotiation schemes involving bandwidth allocation, service start time and service duration parameters are introduced and analyzed. The results show that these negotiation schemes can be utilized for the benefit of both end users and network providers in achieving the highest individual SLA optimization in terms of key Quality of Service (QoS) metrics and price. The inherent characteristics of software agents such as autonomy, adaptability and social abilities offer many advantages in this dynamic, complex, and distributed network environment especially when performing Service Level Agreements (SLA) definition negotiations and brokering tasks. This article also presents a service broker prototype based on Fujitsu's Phoenix Open Agent Mediator (OAM) agent technology, which was used to demonstrate a range of SLA brokering scenarios.

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Just as conventional institutions are organisational structures for coordinating the activities of multiple interacting individuals, electronic institutions provide a computational analogue for coordinating the activities of multiple interacting software agents. In this paper, we argue that open multi-agent systems can be effectively designed and implemented as electronic institutions, for which we provide a comprehensive computational model. More specifically, the paper provides an operational semantics for electronic institutions, specifying the essential data structures, the state representation and the key operations necessary to implement them. We specify the agent workflow structure that is the core component of such electronic institutions and particular instantiations of knowledge representation languages that support the institutional model. In so doing, we provide the first formal account of the electronic institution concept in a rigorous and unambiguous way.

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Risk management in software engineering has become a recognized project management practice but it seems that not all companies are systematically applying it. At the same time, agile methods have become popular, partly because proponents claim that agile methods implicitly reduce risks due
to, for example, more frequent and earlier feedback, shorter periods of development time and easier prediction of cost. Therefore, there is a need to investigate how risk management can be usable in iterative and evolutionary software development processes. This paper investigates the gathering of empirical data on risk management from the project environment and presents
a novel approach to manage risk in agile projects. Our approach is based on a prototype tool, Agile Risk Tool (ART). This tool reduces human effort in risk management by using software agents to identify, assess and monitor risk, based on input and data collected from the project environment and by applying
some designated rules. As validation, groups of student project data were used to provide evidence of the efficacy of this approach. We demonstrate the approach and the feasibility of using a lightweight risk management tool to alert, assess and monitor risk with reduced human effort.

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This paper describes how urban agriculture differs from conventional agriculture not only in the way it engages with the technologies of growing, but also in the choice of crop and the way these are brought to market. The authors propose a new model for understanding these new relationships, which is analogous to a systems view of information technology, namely Hardware-Software- Interface.
The first component of the system is hardware. This is the technological component of the agricultural system. Technology is often thought of as equipment, but its linguistic roots are in ‘technis’ which means ‘know how’. Urban agriculture has to engage new technologies, ones that deal with the scale of operation and its context which is different than rural agriculture. Often the scale is very small, and soils are polluted. There this technology in agriculture could be technical such as aquaponic systems, or could be soil-based agriculture such as allotments, window-boxes, or permaculture. The choice of method does not necessarily determine the crop produced or its efficiency. This is linked to the biotic that is added to the hardware, which is seen as the ‘software’.
The software of the system are the ecological parts of the system. These produce the crop which may or may not be determined by the technology used. For example, a hydroponic system could produce a range of crops, or even fish or edible flowers. Software choice can be driven by ideological preferences such as permaculture, where companion planting is used to reduce disease and pests, or by economic factors such as the local market at a particular time of the year. The monetary value of the ‘software’ is determined by the market. Obviously small, locally produced crops are unlikely to compete against intensive products produced globally, however the value locally might be measured in different ways, and might be sold on a different market. This leads to the final part of the analogy - interface.
The interface is the link between the system and the consumer. In traditional agriculture, there is a tenuous link between the producer of asparagus in Peru and the consumer in Europe. In fact very little of the money spent by the consumer ever reaches the grower. Most of the money is spent on refrigeration, transport and profit for agents and supermarket chains. Local or hyper-local agriculture needs to bypass or circumvent these systems, and be connected more directly to the consumer. This is the interface. In hyper-localised systems effectiveness is often more important than efficiency, and direct links between producer and consumer create new economies.

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Models and software products have been developed for modelling, simulation and prediction of different correlations in materials science, including 1. the correlation between processing parameters and properties in titanium alloys and ?-titanium aluminides; 2. time–temperature–transformation (TTT) diagrams for titanium alloys; 3. corrosion resistance of titanium alloys; 4. surface hardness and microhardness profile of nitrocarburised layers; 5. fatigue stress life (S–N) diagrams for Ti–6Al–4V alloys. The programs are based on trained artificial neural networks. For each particular case appropriate combination of inputs and outputs is chosen. Very good performances of the models are achieved. Graphical user interfaces (GUI) are created for easy use of the models. In addition interactive text versions are developed. The models designed are combined and integrated in software package that is built up on a modular fashion. The software products are available in versions for different platforms including Windows 95/98/2000/NT, UNIX and Apple Macintosh. Description of the software products is given, to demonstrate that they are convenient and powerful tools for practical applications in solving various problems in materials science. Examples for optimisation of the alloy compositions, processing parameters and working conditions are illustrated. An option for use of the software in materials selection procedure is described.

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