AI 中文总结
本文针对测试结果被作弊者污染的问题，提出采用动态规划确定的最优测试策略，通过重测选定组并使用不同安全措施，以恢复诚实测试结果。
AI 中文摘要
在各类应用中，常需对对象或人员进行测试以确定其在特定指标下的属性。然而，除了天然存在的噪声外，测试结果还可能被被测对象或人员（测试参与者）的对抗性行为破坏，例如不诚实的测试参与者可在考试中作弊以扭曲测试结果。随着AI技术发展，此类由AI作弊驱动的扭曲愈发普遍且严重。本文提出最优测试策略，即便存在作弊者污染结果，仍能恢复所需测试结果；该策略将采用不同测试安全措施，对选定的测试参与者组进行最优重测，我们使用动态规划方法确定最优测试策略。
英文摘要
In applications, it is often required to test objects or people to determine their qualities in terms of certain metrics. However, besides being naturally noisy, the test results can be corrupted by adversarial behaviors of objects or people being tested (test takers). For example, dishonest test takers can cheat in the exams to distort the test results. With the development of AI technologies, such distortions driven by cheating using AI technologies are becoming more commonplace and severe. In this paper, we propose optimal testing strategies which can still recover needed test results even if there are cheaters polluting the results. The proposed testing strategies will optimally re-test selected group of test takers using different testing security measures. We determine the optimal testing strategies using a dynamic programming method.
Comments9 pages
