BSF:2012144:Human-Competitive Evolutionary Computation

该项目是美国-以色列计算机科学合作（USICCS）计划的一部分。通过这个项目，NSF和美国-以色列两国科学基金会（BSF）共同支持美国科学家和以色列科学家之间的合作。该项目将研究和扩展计算技术，使计算机在某些类型的难题上胜过人类，其中一些在许多科学和工程领域都有实际应用。被研究的技术以生物进化过程为模型，已经被证明在从纯数学到量子系统设计，从游戏系统到软件工程和调试等领域产生与人类竞争的表现。在这个项目中，共同项目负责人将合作描述这些人类竞争成功的应用领域，以及在每个案例中使用的具体技术。该项目将使用这些特征来指导技术的改进和新问题的应用。这项研究的初始数据将取自人类竞争结果竞赛的获胜者，该竞赛自2004年以来每年在遗传与进化计算会议上举行。预期应用程序工作的领域包括软件工程，例如自动程序合成和修复，其中早期的成功和潜在应用程序的规模表明了实质性的承诺。这一领域工作的长期潜力是计算机自动生成有用的软件，用于许多具有科学或社会意义的应用，这对于人类程序员来说是非常困难或昂贵的。该项目将与本科生和研究生一起进行，从而也将有助于培养未来的计算机科学创新者。

This project is funded as part of the United States-Israel Collaboration in Computer Science (USICCS) program. Through this program, NSF and the United States - Israel Binational Science Foundation (BSF) jointly support collaborations among US-based researchers and Israel-based researchers.This project will examine and extend computational techniques that allow computers to out-perform humans on certain classes of difficult problems, some of which have practical applications across many areas of science and engineering. The techniques to be studied, which are modeled on biological processes of evolution, have already been shown to produce human-competitive performance in areas ranging from pure mathematics to quantum system design, and from game-playing systems to software engineering and debugging. In this project the co-PIs will collaborate to characterize the application areas in which these human-competitive successes have been achieved, along with the specific techniques that were used in each case. The project will use these characterizations to guide improvements to the techniques and applications to new problems.The initial data for the study will be taken from the winners of the of the Human Competitive Results Competition that has been held annually since 2004 at the Genetic and Evolutionary Computation Conference. Areas of anticipated application work include software engineering, for example for automatic program synthesis and repair, where early successes and the scale of the potential applications indicate substantial promise. The long-term potential of work in this area is for computers to automatically generate useful software, for many applications of scientific or social significance, that would be prohibitively difficult or expensive for human programmers to produce. The project will be conducted with undergraduates and graduate students and will also thereby help to train future innovators in computer science.