5 0 0 0 OA 合理性の地図:歴史的・理論的観点からの考察
- 著者
- 中村 國則 斎藤 元幸
- 出版者
- 日本認知科学会
- 雑誌
- 認知科学 (ISSN:13417924)
- 巻号頁・発行日
- vol.29, no.3, pp.446-460, 2022-09-01 (Released:2022-09-15)
- 参考文献数
- 105
Rationality has been one of the most important theoretical concepts in cognitive science. Up until now, plenty of rationality concepts have been proposed to represent human decision-making processes. This paper aims to draw a map of rationality in psychology and cognitive sciences literature by clarifying their theoretical features, functions, and similarities. In doing so, this paper reviewed many rationality concepts proposed in the pieces of literature on higher cognition, including reasoning or judgment and decision making. It explained how these rationality concepts explained biases in human thinking and how they have changed through a history of judgment and decision-making research. This paper pointed out that rationality is now considered the goal of or evidence for cognitive model and that recent rationality concepts treat decision making as resolving trade-off between plural conflicting aims such as expected utility and computational efficiency, through the review of rationality concept in reasoning and judgment and decision-making literature.
5 0 0 0 OA 因果性の学習と推論における因果ベイズネットについて
- 著者
- 斎藤 元幸
- 出版者
- 日本認知科学会
- 雑誌
- 認知科学 (ISSN:13417924)
- 巻号頁・発行日
- vol.24, no.1, pp.79-95, 2017-03-01 (Released:2017-09-01)
- 参考文献数
- 106
- 被引用文献数
- 1
Causal knowledge enables us to explain past events, to control present environment,and to predict future outcomes. Over the last decade, causal Bayes nets have been rec-ognized as a normative framework for causality and used as a psychological model to account for human causal learning and inference. This article provides an introduction to causal Bayes nets. According to causal Bayes nets, causal inference can be divided into three processes: (a) learning the structure of the causal network, (b) learning the strength of the causal relations, and (c) inferring the effect from the cause or the cause from the effect. For each process, I describe the predictions of causal Bayes nets, review experimental results, and suggest future directions. Although there are a few excep-tions (e.g., Markov violation), most of the results are consistent with the predictions of causal Bayes nets. The current problems of the Bayesian approach and its future perspective are discussed.
3 0 0 0 OA 因果推論におけるパワーPC 理論について
- 著者
- 斎藤 元幸 嶋崎 恒雄 Motoyuki Saito Tsuneo Shimazaki
- 雑誌
- 人文論究 (ISSN:02866773)
- 巻号頁・発行日
- vol.59, no.3, pp.1-21, 2009-12-10