An Integrative Framework for Artificial Intelligence Education
An Integrative Framework for Artificial Intelligence Education
复制标题
人工智能教育综合框架
DOI：
10.1609/aaai.v33i01.33019670
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发表时间：
2019
期刊：
影响因子：
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通讯作者：
P. Langley
中科院分区：
文献类型：
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作者：
P. Langley
关于人工智能的现代入门课程并没有训练学生创建智能系统，也没有提供这个复杂领域的广泛覆盖。在本文中，我们确定了教授人工智能的常见方法存在的问题，并提出了课程应该采用的替代原则。我们说明了这些原则，在建议的课程，教学生不仅组件的方法，如模式匹配和决策，但也对他们的组合成更高层次的推理能力，顺序控制，计划生成，和集成的智能代理。我们还提出了一个课程，实例化这个组织，包括示例编程练习和一个项目，需要系统集成。参与者还获得了构建基于知识的代理的经验，这些代理使用他们的软件来产生智能行为。
Modern introductory courses on AI do not train students to create intelligent systems or provide broad coverage of this complex field. In this paper, we identify problems with common approaches to teaching artificial intelligence and suggest alternative principles that courses should adopt instead. We illustrate these principles in a proposed course that teaches students not only about component methods, such as pattern matching and decision making, but also about their combination into higher-level abilities for reasoning, sequential control, plan generation, and integrated intelligent agents. We also present a curriculum that instantiates this organization, including sample programming exercises and a project that requires system integration. Participants also gain experience building knowledge-based agents that use their software to produce intelligent behavior.