期刊文献+

基于因果关系的人工智能 被引量:1

On the Causality-Based Artificial Intelligence
下载PDF
导出
摘要 当前,新一代人工智能,特别是具有可解释性的基于因果关系的人工智能成为领域关注点。图灵奖获得者朱迪亚·珀尔(Judea Pearl)的因果贝叶斯网络模型成为研究热点。本文简要分析了因果贝叶斯网络与贝叶斯网络的关系、存在的缺点,进而介绍了笔者原创的动态不确定因果图(Dynamic Uncertain Causality Graph,DUCG)模型及其优点,以及目前的应用情况。
作者 张勤 ZHANG Qin
出处 《军事运筹与评估》 2022年第3期5-9,共5页 Military Operations Research and Assessments
  • 相关文献

二级参考文献31

  • 1Lucas P J F. Bayesian network modeling through qualitative patterns. Artificial Intelligence, 2005, 163(2): 233-263.
  • 2Shortliffe E H, Buchanan B G. A model of inexact reason in medicine. Mathematical Bioscience, 1975, 23(3/4): 351-379.
  • 3Sharer G. A Mathematical Theory of Evidence. Princeton, N J: Princeton University Press, 1976.
  • 4Duda R O et al. Development of the Prospector consultation system for mineral exploration. Final report, SRI Project 5821 and 6415, SRI International, 1978.
  • 5Zadeh L A. The role of fuzzy logic in the management of un- certainty in expert systems. Fuzzy Sets and Systems, 1983, 11: 199-227.
  • 6Pearl J. Fusion, propagation, and structuring in belief net- works. Artificial Intelligence, 1986, 29(3): 241-288.
  • 7Pearl J. Probabilistic Reasoning in Intelligent Systems. San Mateo: Morgan Kaufmann, 1988. ISBN 0-934613-73-7.
  • 8Henrion M. Practical issues in constructing a Bayes' belief network. In Proc. the 3rd Conf. Uncertainty in Artificial Intelligence, July 1987, pp.132-139.
  • 9Srinivas S. A generalization of the noisy-OR model. In Proe. the 9th Conf. Uncertainty in Artificial Intelligence, San Fran- cisco, July 1993, pp.208-215.
  • 10Diez F J. Parameter adjustment in Bayes networks: The gen- eralized noisy-OR gate. In Proc. the 9th Conf. Uncertainty in Artificial Intelliqence, 1993, pp.99-105.

共引文献24

同被引文献7

引证文献1

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部