Inductive Inference and other topics in the Foundations of Computing (Computer and Information Science)

这个项目是为了在计算的基础上进行基础研究。主要的重点是归纳推理领域，即计算机通过示例学习的能力和局限性。将研究涉及多机推理、概率推理和推理复杂性的几个问题。归纳推理问题与程序测试问题有关。将归纳推理领域的思想和技术继续输出到与程序测试有关的应用程序将是本研究的主要重点。正在研究的其他问题包括与数据流体系结构和应用编程语言的实现有关的基本问题。关于抽象复杂性理论的问题和问题，已经从先前的NSF项目的前期工作中暴露出来。本研究解决的基本问题是对适用于给定编程系统的复杂性度量空间进行分类和界定。

This project is for basic research in the foundations of computing. The major emphasis is in the area of inductive inference, the capabilities and limitations of computers to learn by example. Several problems dealing with multiple machine inference, probabilistic inference, and the complexity of inference will be studied. The problem of inductive inference is related to the problem of program testing. The continued exportation of ideas and techniques from the field of inductive inference to applications concerning the testing of programs will be a main focus of this research. Other problems under study include foundational issues concerning data flow architectures and implementations of applicative programming languages. Issues and problems concerning abstract complexity theory have come out of the preliminary work of a previous NSF project. The fundamental problem addressed in this research is to classify and otherwise delimit the space of complexity measures that apply to a given programming system.