Parallel Computation and Learning

并行计算与学习

• 批准号: 8902500
• 负责人: Leslie Valiant
• 金额: $ 34万
• 依托单位: Harvard University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 1989
• 资助国家: 美国
• 起止时间: 1989-08-01 至 1992-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=8902500&HistoricalAwards=false
• 关键词: Parallel; Computation; Learning

The project is concerned with developing and applying ideas from complexity theory to three distinct but related areas of computation: Under continued investigation are the theoretical possibilities for general purpose parallel computers. The problem is to devise idealised high level models that are both convenient for the programmer as well as efficiently simulated in realistic technologies. As a distinct topic in parallel computation the computational capabilities of brainlike models of computation are being studied. Such neural models appear to become more distinct from other complexity models if biologically plausible restrictions on time and space resources are imposed. Thirdly, partly in support of this latter work, the PI will continue to investigate the limits of what can be learned or induced, as imposed by such criteria as polynomial time computability.

该项目涉及开发和应用来自 复杂性理论到三个不同但相关的计算领域： 在继续调查的理论可能性， 通用并行计算机 问题是设计出理想化的 高级模型，既方便程序员， 在现实技术中被有效地模拟。 作为一个独特 并行计算的计算能力 类脑计算模型正在研究中。 这样的神经模型 似乎变得更加不同于其他复杂性模型， 生物学上合理的时间和空间资源限制， 强加的 第三，为支持后一项工作，PI将 继续研究可以学习或诱导的极限， 这是由诸如多项式时间可计算性的标准所强加的。