BSF:2012144:Human-Competitive Evolutionary Computation
BSF:2012144:人类竞争进化计算
基本信息
- 批准号:1331283
- 负责人:
- 金额:$ 4.2万
- 依托单位:
- 依托单位国家:美国
- 项目类别:Standard Grant
- 财政年份:2013
- 资助国家:美国
- 起止时间:2013-10-01 至 2017-09-30
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
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.
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)共同支持美国和以色列研究人员之间的合作。这个项目将研究和扩展计算技术,使计算机能够在某些类别的困难问题上超越人类,其中一些在许多科学和工程领域都有实际应用。这些以生物进化过程为模型的技术已经被证明可以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人类竞争力。在这个项目中,合作PI将合作描述这些人类竞争成功的应用领域,沿着在每种情况下使用的特定技术。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。该研究的初始数据将来自人类竞争结果竞赛的获胜者,该竞赛自2004年以来每年在遗传和进化计算会议上举行。预期的应用工作领域包括软件工程,例如自动程序合成和修复,早期的成功和潜在应用的规模表明了巨大的希望。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。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Lee Spector其他文献
Expressive genetic programming: tutorial: 2012 genetic and evolutionary computation conference (GECCO-2012)
表达性遗传编程:教程:2012 年遗传与进化计算会议 (GECCO-2012)
- DOI:
- 发表时间:
2012 - 期刊:
- 影响因子:0
- 作者:
Lee Spector - 通讯作者:
Lee Spector
Objectives Are All You Need: Solving Deceptive Problems Without Explicit Diversity Maintenance
您所需要的就是目标:在没有明确的多样性维护的情况下解决欺骗性问题
- DOI:
- 发表时间:
2023 - 期刊:
- 影响因子:0
- 作者:
Ryan Boldi;Lijie Ding;Lee Spector - 通讯作者:
Lee Spector
Relationships between parent selection methods, looping constructs, and success rate in genetic programming
- DOI:
10.1007/s10710-021-09417-5 - 发表时间:
2021-09-30 - 期刊:
- 影响因子:0.900
- 作者:
Anil Kumar Saini;Lee Spector - 通讯作者:
Lee Spector
Pareto-Optimal Learning from Preferences with Hidden Context
从具有隐藏上下文的偏好中进行帕累托最优学习
- DOI:
- 发表时间:
2024 - 期刊:
- 影响因子:0
- 作者:
Ryan Boldi;Lijie Ding;Lee Spector;S. Niekum - 通讯作者:
S. Niekum
Introduction to the peer commentary special section on “On the Mapping of Genotype to Phenotype in Evolutionary Algorithms” by Peter A. Whigham, Grant Dick, and James Maclaurin
- DOI:
10.1007/s10710-017-9287-y - 发表时间:
2017-02-23 - 期刊:
- 影响因子:0.900
- 作者:
Lee Spector - 通讯作者:
Lee Spector
Lee Spector的其他文献
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{{ truncateString('Lee Spector', 18)}}的其他基金
RI: Small: RUI: Synthesis of Robust Artificial Systems by Adaptive Genetic Programming
RI:小型:RUI:通过自适应遗传编程合成稳健的人工系统
- 批准号:
1617087 - 财政年份:2016
- 资助金额:
$ 4.2万 - 项目类别:
Standard Grant
UBM-Institutional-Collaborative Research: Four College Biomath Consortium
UBM-机构合作研究:四所大学生物数学联盟
- 批准号:
1129139 - 财政年份:2011
- 资助金额:
$ 4.2万 - 项目类别:
Standard Grant
RI: Small: RUI: Evolution of Robustly Intelligent Computational Systems
RI:小型:RUI:鲁棒智能计算系统的演变
- 批准号:
1017817 - 财政年份:2010
- 资助金额:
$ 4.2万 - 项目类别:
Standard Grant
Open-Ended Evolution in Visually Rich Virtual Worlds: Implementation, Analysis, and Use in Undergraduate Education
视觉丰富的虚拟世界中的开放式进化:本科教育中的实施、分析和使用
- 批准号:
0308540 - 财政年份:2003
- 资助金额:
$ 4.2万 - 项目类别:
Standard Grant
MRI/RUI: Acquisition of Instrumentation for Research in Genetic Programming, Quantum Computation, and Distributed Systems
MRI/RUI:采购用于基因编程、量子计算和分布式系统研究的仪器
- 批准号:
0216344 - 财政年份:2002
- 资助金额:
$ 4.2万 - 项目类别:
Standard Grant