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A rule-based agent-oriented approach for supporting weakly-structured scientific workflows

机译:基于规则的面向代理的方法,用于支持结构较弱的科学工作流

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Weakly-structured Scientific Workflows (WsSWFs) often contain goal-oriented tasks that are logical and complicated, but they are vital for workflow results. They may involve interactions between multiple participants or have complicated logic to express scientific policies and cater to dynamic execution environments. In general, such WsSWFs not only need a rich process and (domain-specific) decision logic specification, but also require a flexible execution and human interaction. In this paper, we propose a Rule-based Agent-oriented Framework (RbAF) to support the WsSWF execution by combining rule-based knowledge representation with agent technology. We describe workflows by messaging reaction rules, which go beyond global Event-Condition-Action (ECA) rules and support performing complex actions locally within certain contexts. We describe (domain-specific) decision logic in workflows by exploiting the benefits of both Logic Programming (LP) and Description Logic (DL). Our evaluation results show that, RbAF well supports the WsSWFs and has higher expressive power than other three considered scientific workflow systems. (C) 2016 Elsevier B.V. All rights reserved.
机译:弱结构的科学工作流(WsSWF)通常包含逻辑上和复杂的面向目标的任务,但它们对于工作流结果至关重要。它们可能涉及多个参与者之间的交互,或者具有复杂的逻辑来表达科学政策并迎合动态执行环境。通常,此类WsSWF不仅需要丰富的流程和(特定于域的)决策逻辑规范,而且还需要灵活的执行和人工交互。在本文中,我们提出了一种基于规则的面向代理的框架(RbAF),通过将基于规则的知识表示与代理技术相结合来支持WsSWF的执行。我们通过消息传递反应规则来描述工作流,该规则超越了全局事件-条件-动作(ECA)规则,并支持在特定上下文中本地执行复杂的动作。我们通过利用逻辑编程(LP)和描述逻辑(DL)的优势来描述工作流中(特定于域的)决策逻辑。我们的评估结果表明,RbAF很好地支持WsSWF,并且比其他三个被认为科学的工作流程系统具有更高的表达能力。 (C)2016 Elsevier B.V.保留所有权利。

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