Applications development using a hybrid ai development system
Applications development using a hybrid ai development system
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使用混合人工智能开发系统进行应用程序开发
DOI：
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发表时间：
1987
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通讯作者：
M. Williams
中科院分区：
文献类型：
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作者：
J. Kunz;T. Kehler;M. Williams
本文描述了我们在混合人工智能工具环境中构建应用程序的初步经验。传统的系统开发强调单一的方法，如框架、规则或逻辑编程，作为一种自然、高效和统一的方法。我们开发的应用表明，自然、效率和灵活性都是通过交换统一性来提高的，而统一性是由一小组适当的编程和表示工具提供的。我们使用的工具基于五种主要的人工智能方法：具有继承的基于框架的知识表示、基于规则的推理、LISP、交互式图形和动态值——面向对象计算为在单个系统中统一这些不同的方法提供了一个原则。由于我们的应用程序开发经验，我们开始使用一种开发方法，强调早期原型开发、问题描述的增量细化、使用多种集成的解决方案方法，并强调问题解决过程的可见性和问题域的明确描述。使用这种混合开发方法的好处包括自然和明确的知识表示，灵活的用户-系统交互，以及通过使用交互式图形提供的强大的解释工具。我们举一个例子来激发我们的讨论。人工智能的工作人员通常对一种编程方法表现出强烈的偏好，而不是其他所有方法，例如规则(例如，在一个
Abstract Argument for Hybridization This article describes our initial experience with building applications programs in a hybrid AI tool environment. Traditional systems developments have emphasized a single methodology, such as frames, rules, or logic programming, as a methodology that is natural, efficient, and uniform The applications we have developed suggest that natural- ness, efficiency and flexibility are all increased by trading uniformity for the power that is provided by a small set of appropriate program- ming and representation tools The tools we use are based on five major AI methodologies: frame-based knowledge representation with inheritance, rule-based reasoning, LISP, interactive graphics, and ac- tive values Object-oriented computing provides a principle for unifying these different methodologies within a single system. As a result of our applications development experiences, we are beginning to use a development methodology that emphasizes early prototype development, incremental refine- ment of the problem description, use of multiple integrated solution methods, and emphasis on visibility of both the problem-solution process and the explicit description of the problem domain. The benefits of using this hybrid develop- ment methodology include natural and explicit knowledge representations, flexible user-system interaction, and power- ful explanation facilities through use of interactive graphics. We present an example to motivate our discussion. Workers in AI often express a strong preference for one programming methodology over all others, such as rules (e.g., within an