Case-by-Case Problem Solving

被引：0
|
作者：
Pei Wang [1 ]
机构：
[1] Temple Univ, Philadelphia, PA 19122 USA
来源：
ARTIFICIAL GENERAL INTELLIGENCE PROCEEDINGS | 2009年 / 8卷
关键词：
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Case-by-case Problem Solving solves each occurrence, or case, of a problem using available knowledge and resources on the case. It is different from the traditional Algorithmic Problem Solving, which applies the same algorithm to all occurrences of all problem instances. Case-by-case Problem Solving is suitable for situations where the system has no applicable algorithm for a problem. This approach gives the system flexibility, originality, and scalability, at the cost of predictability. This paper introduces the basic notion of Case-by-case Problem Solving, as well as its most recent implementation in NARS, an AGI project.
引用
收藏
页码：180 / 185
页数：6
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