Autonomous Agents: An Advanced Course on AI Integration and Deployment

Stephanie Rosenthal, R. Simmons
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Abstract

A majority of the courses on autonomous systems focus on robotics, despite the growing use of autonomous agents in a wide spectrum of applications, from smart homes to intelligent traffic control. Our goal in designing a new senior-level undergraduate course is to teach the integration of a variety of AI techniques in uncertain environments, without the dependence on topics such as robotic control and localization. We chose the application of an autonomous greenhouse to frame our discussions and our student projects because of the greenhouse's self-contained nature and objective metrics for successfully growing plants. We detail our curriculum design, including lecture topics and assignments, and our iterative process for updating the course over the last four years. Finally, we present some student feedback about the course and opportunities for future improvement.
自主代理:人工智能集成与部署高级课程
尽管从智能家居到智能交通控制等广泛应用中越来越多地使用自主代理,但大多数关于自主系统的课程都侧重于机器人技术。我们设计一门新的高级本科课程的目标是教授各种人工智能技术在不确定环境中的集成,而不依赖于机器人控制和定位等主题。我们选择了一个自主温室来框架我们的讨论和我们的学生项目,因为温室的自成一体的性质和成功种植植物的客观指标。我们详细介绍了我们的课程设计,包括讲座主题和作业,以及我们在过去四年中更新课程的迭代过程。最后,我们提出了一些学生对课程的反馈和未来改进的机会。
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