CAREER: Evaluation as the Basis for AI Agent Design

许多软件开发人员认为评估是一种负担，因为它目前需要付出巨大的努力，而且大多数程序员都没有接受过这方面的培训。在国际人工智能专业领域(人工智能的规划和代理设计)的背景下，本项目的目的是解决当前方法和教学中的两个空白：缺乏人工智能软件代理的评估方法，以及本科生和研究生计算机科学课程中缺乏经验和评估方法。为此，研究部分创建了新的评估方法，支持在两个代理项目的背景下进行人工智能代理的设计和开发：一个模拟机器人和一个万维网信息收集代理。教学部分将评估方法纳入本科生和研究生计算机科学课程，在可能的情况下将单元纳入现有课程，并在必要时设计新的课程。每个组件利用现有的和新的研究项目来探索激励设计中的评估问题。预期的结果不仅是新的软件评估方法、它们的使用记录实例和两个全面评估的软件代理，而且还包括经验丰富的新实践者。

Many software developers view evaluation as a burden both because it currently takes significant effort and because most programmers are not trained in it. In the context of the PI's area of expertise (planning and agent design in Artificial Intelligence), the purpose of this project is to address two gaps in current methodology and pedagogy: the dearth of evaluation methods for AI software agents and the absence of empirical and evaluation methods in the undergraduate and graduate computer science curricula. Towards these ends, the research component creates new methods for evaluation that support AI agent design and development in the context of two agent projects: a simulated robot and an information gathering agent for the WWW. The teaching component integrates evaluation methods into the undergraduate and graduate CS curriculum by incorporating modules into existing courses where possible and designing new courses where necessary. Each component exploits existing and new research projects for exploring issues of evaluation in motivating design. The expected results are not only new software evaluation methods, documented examples of their use and two thoroughly evaluated software agents, but also experienced, new practitioners.