Practical Competitive Analysis (Computer Science)

如果一个算法在一系列请求中接收到输入，并且必须在不知道未来的情况下为每个请求提供服务，则该算法被称为在线。 计算机科学中的许多基本问题本质上都是在线的。 分析在线算法的常用方法是竞争分析，其中将在线算法的性能与最佳透视算法的性能进行比较。 通常的竞争分析风格有几个实际问题，包括 使用最坏的照顾对手，缺乏对执行效率的关注，以及缺乏关于竞争算法性能的经验证据。 这个项目的目标是帮助弥合理论和实践之间的差距，在这个快速增长的领域，通过开发有效的，自适应算法的基本系统问题。 这些算法应该对统计对手表现良好，并将进行经验评估。 互动活动包括：参与妇女参与工程的指导和推广方案;通过与华盛顿大学Steve Tanimoto教授的研究小组和不列颠哥伦比亚省Maria Klawe教授的E-GEMS项目合作，开发和试验女孩数学教学软件;教授计算机科学的本科课程和研讨会，并与华盛顿大学计算机科学系的其他成员进行联合研究。

An algorithm is said to be online if it receives input in a sequence of requests, and must service each request as it arrives without any knowledge of the future. Many fundamental problems in computer science are inherently online. A commonly used method of analyzing online algorithms is competitive analysis, where the performance of the online algorithm is compared to the performance of the optimal clairvoyant algorithm. There are several practical problems with the usual style of competitive analysis, including the use of worst care adversary, the lack of attention to implementation efficiency, and the lack of empirical evidence concerning the performance of competitive algorithms. The goal of this project is to help bridge the gap between theory and practice in this rapidly growing area by developing efficient, adaptive algorithms for fundamental systems problems. These algorithms should perform well against a statistical adversary, and will be empirically evaluated. Interactive activities include: participation in the mentoring and outreach programs of Women in Engineering; development of and experimentation with software for teaching math to girls, via collaboration with Professor Steve Tanimoto's research group at the University of Washington (UW) and with Professor Maria Klawe's E- GEMS project at the University of British Columbia; and teaching an undergraduate course and seminars in computer science and undertaking joint research with other members of the computer science faculty at UW.