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Generating Knowledge-Based System Generators:A Software Engineering Approach

机译:生成基于知识的系统生成器:一种软件工程方法

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This article investigates software engineering techniques for designing and reengineering knowledge-based system generators, focusing on inference engines and domain specific languages. Indeed, software development ofknowledge-based systems is a difficult task. We choose a software engineering approach to favor code reuse, evolution, and maintenance. We propose a software platform named LAMA to design the different elements necessary to produce a knowledge-based system. This platform offers software toolkits (mainly component frameworks) to build interfaces, inference engines, and expert languages. We have used the platform to build several KBS generators for various tasks (planning, classification, model calibration) in different domains. The approach appears well fitted to knowledge-based system generators; it allows developers a significant gain in time, as well as it improves software readability and safeness.
机译:本文研究了用于设计和重新设计基于知识的系统生成器的软件工程技术,重点是推理引擎和领域特定的语言。实际上,基于知识的系统的软件开发是一项艰巨的任务。我们选择一种软件工程方法来支持代码重用,演化和维护。我们提出一个名为LAMA的软件平台,以设计生产基于知识的系统所需的不同元素。该平台提供了用于构建接口,推理引擎和专家语言的软件工具包(主要是组件框架)。我们已经使用该平台为不同领域的各种任务(计划,分类,模型校准)构建了多个KBS生成器。该方法似乎非常适合基于知识的系统生成器;它使开发人员可以节省大量时间,并提高了软件的可读性和安全性。

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