...
  • 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Psychological Review >Constraints and nonconstraints in causal learning: Reply to White (2005) and to Luhmann and Ahn (2005)
【24h】

Constraints and nonconstraints in causal learning: Reply to White (2005) and to Luhmann and Ahn (2005)

机译：因果学习中的约束和非约束：答复怀特（2005）以及卢曼和安（2005）

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

The task of causal learning concerns figuring out the laws that govern how the world works. The goal of a reasoner who engages in this task is to gain an understanding of the empirical world that would guide decisions regarding actions to achieve the reasoner's objectives. The comments by P. A. White (2005) and C. Luhmann and W.-k. Alin (2005) on P. W. Cheng (1997) and L. R. Novick and P. W. Cheng's (2004) power PC theory of causal learning do not define the constraints of the task of causal learning in the same way as does that theory: They change constraints on the input and omit consideration of the goal. This article clarifies the approach taken by the power PC theory to address the issues raised. In particular, it illustrates how the approach provides a framework for answering causal questions under various assumptions-a framework that allows the incremental construction of a causal picture of a complex world.
机译：因果学习的任务涉及弄清楚控制世界运作方式的法律。从事此任务的推理机的目标是获得对经验世界的理解，该经验世界将指导有关为实现推理机目标而采取的行动的决策。 P. A. White（2005）和C. Luhmann和W.-k的评论。关于PW Cheng（1997）和LR Novick和PW Cheng（2004）的因果学习的Power PC理论的Alin（2005）没有以与该理论相同的方式定义因果学习任务的约束：他们改变了因果学习的约束输入和忽略对目标的考虑。本文阐明了功率PC理论用于解决所提出问题的方法。特别是，它说明了该方法如何提供在各种假设下回答因果问题的框架，该框架允许逐步构建复杂世界的因果图。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号