How do people learn from negative evidence? Non-monotonic generalizations and sampling assumptions in inductive reasoning
详细信息 查看全文
- 作者：Wouter Voorspoelsa ; wouter.voorspoels@ppw.kuleuven.be" class="auth_mail" title="E-mail the corresponding author ; Daniel J. Navarrob ; daniel.navarro@adelaide.edu.au" class="auth_mail" title="E-mail the corresponding author ; Amy Perforsb ; amy.perfors@adelaide.edu.au" class="auth_mail" title="E-mail the corresponding author ; Keith Ransomb ; keith.ransom@adelaide.edu.au" class="auth_mail" title="E-mail the corresponding author ; Gert Stormsa ; gert.storms@ppw.kuleuven.be" class="auth_mail" title="E-mail the corresponding author
- 关键词：Inductive reasoning ; Relevance ; Negative evidence ; Sampling assumptions ; Bayesian inference
- 刊名：Cognitive Psychology
- 出版年：2015
- 出版时间：September 2015
- 年：2015
- 卷：81
- 期：Complete
- 页码：1-25
- 全文大小：952 K
文摘
- bel">•
We examine category-based inductive inference involving negative observations.
- bel">•
We find that negative observations can raise the willingness to generalize.
- bel">•
This occurs when a reasoner assumes that the observations were selected to be helpful.
- bel">•
We propose a theoretical account, in form of a Bayesian model.
- bel">•
The model explains when and why negative observations can facilitate generalization.