Issues in Temporal and Causal Inference

被引：6

作者：

Wang, Pei ^{[1
]}

Hammer, Patrick ^{[2
]}

机构：

[1] Temple Univ, Dept Comp & Informat Sci, Philadelphia, PA 19122 USA

[2] Graz Univ Technol, Inst Optimizat & Discrete Math, A-8010 Graz, Austria

来源：

ARTIFICIAL GENERAL INTELLIGENCE (AGI 2015) | 2015年 / 9205卷

关键词：

D O I：

10.1007/978-3-319-21365-1_22

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This paper discusses several key issues in temporal and causal inference in the context of AGI. The main conclusions are: (1) the representation of temporal information should take multiple forms; (2) classical conditioning can be carried out as temporal inference; (3) causal inference can be realized without a predefined causal relation.

引用

页码：208 / 217

页数：10

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