There is a need for integrated thinking about causality, probability and mechanisms in
scientific methodology. Causality and probability are long-established central concepts in …

There is a need for integrated thinking about causality, probability and mechanisms in
scientific methodology. Causality and probability are long-established central concepts in …

There is a need for integrated thinking about causality, probability and mechanisms in
scientific methodology. Causality and probability are long-established central concepts in …

Causality in the sciences | CiNii Research CiNii 国立情報学研究所 学術情報ナビゲータ[サイニィ]
詳細へ移動 検索フォームへ移動 論文・データをさがす 大学図書館の本をさがす 日本の博士論文を …

Why do ideas of how mechanisms relate to causality and probability differ so much across
the sciences? Can progress in understanding the tools of causal inference in some sciences …

This paper presents a general theory of causation based on the Structural Causal Model
(SCM) described in (Pearl, 2000a). The theory subsumes and unifies current approaches to …

We propose an empirical explication of the notion of 'causation', which we call a generalized
explication of 'causation'(GEC), based on the numerical balance between instantiations of …

There is a need for integrated thinking about causality, probability and mechanisms in
scientific methodology. Causality and probability are long-established central concepts in …

Abstract The principle of Kolmogorov Minimal Sufficient Statistic (KMSS) states that the
meaningful information of data is given by the regularities in the data. The KMSS is the …

There is a need for integrated thinking about causality, probability and mechanisms in
scientific methodology. Causality and probability are long-established central concepts in …