Computational Rationality

计算理性

• 批准号: 9504436
• 负责人: Leslie Valiant
• 金额: $ 29.05万
• 依托单位: Harvard University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 1995
• 资助国家: 美国
• 起止时间: 1995-09-01 至 2000-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9504436&HistoricalAwards=false
• 关键词: Computational; Rationality

In computational studies of intelligent behavior several phenomena have been isolated, among the most important of which are learning, reasoning, and planning. Obstacles that have been found pervasive are that the formalization of the various phenomena are often inconsistent with each other, and, even more often, that they are computationally intractable. This main thrust of this research project is to develop a computational framework and some algorithms that would comprise a unified approach to this problem area. The proposed starting point is the idea that the concept of probably approximately correct (PAC) learning provides a quantitative criterion on the behavioral performance of a system. These analytic methods used in computational learning theory, are extended to a wider class of phenomena, including various notions of reasoning and planning.

在智能行为的计算研究中，一些现象被分离出来，其中最重要的是学习、推理和规划。 人们发现普遍存在的障碍是各种现象的形式化往往彼此不一致，而且更常见的是它们在计算上难以处理。 该研究项目的主要目标是开发一个计算框架和一些算法，以构成解决该问题领域的统一方法。 所提出的出发点是这样的想法：可能近似正确（PAC）学习的概念为系统的行为性能提供了定量标准。 计算学习理论中使用的这些分析方法被扩展到更广泛的现象，包括推理和规划的各种概念。