Add to ORKGThere are too many theories of causation to get into the focus of a small paper. But there are two in which I have a natural interest since they look almost the same: namely the theory of Clark Glymour, Peter Spirtes, and Richard Scheines, so vi-gorously developed since 19831 and most richly stated in Spirtes et al. (1993
Humans possess considerable causal knowledge about the world. For example, one might have beliefs ab...
Alexander Gebharter (2017b) has proposed to use Bayesian network (BN) causal discovery methods to i...
Titans like Bertrand Russell or Karl Pearson warned us to keep ourmathematical and statistical hands...
The paper displays the similarity between the theory of probabilistic causation developed by Glymour...
Abstract. Bayes nets are seeing increasing use in expert systems [2, 6], and structural equations mo...
We start this paper by arguing that causality should, in analogy with force in Newtonian physics, be...
The causal Bayes net framework specifies a set of axioms for causal discovery. This article explores...
This paper suggests a revision of the theory of causal nets (TCN). In Section 1 we introduce an axio...
[Introduction] 'Causal modelling' is a general term that applies to a wide variety of formal method...
Newsome ((2003). The debate between current versions of covariation and mechanism approaches to caus...
Newsome ((2003). The debate between current versions of covariation and mechanism approaches to caus...
There are many theories of causation, and each has its virtues. If it is to be understood why knowle...
this paper another misguided attempt to reduce causation to probability. But causation leaves a dist...
In this paper we show that the application of Oc-cam’s razor to the theory of causal Bayes nets give...
Four theories proposing determinate relations of actual causation for Boolean networks are described...
Humans possess considerable causal knowledge about the world. For example, one might have beliefs ab...
Alexander Gebharter (2017b) has proposed to use Bayesian network (BN) causal discovery methods to i...
Titans like Bertrand Russell or Karl Pearson warned us to keep ourmathematical and statistical hands...
The paper displays the similarity between the theory of probabilistic causation developed by Glymour...
Abstract. Bayes nets are seeing increasing use in expert systems [2, 6], and structural equations mo...
We start this paper by arguing that causality should, in analogy with force in Newtonian physics, be...
The causal Bayes net framework specifies a set of axioms for causal discovery. This article explores...
This paper suggests a revision of the theory of causal nets (TCN). In Section 1 we introduce an axio...
[Introduction] 'Causal modelling' is a general term that applies to a wide variety of formal method...
Newsome ((2003). The debate between current versions of covariation and mechanism approaches to caus...
Newsome ((2003). The debate between current versions of covariation and mechanism approaches to caus...
There are many theories of causation, and each has its virtues. If it is to be understood why knowle...
this paper another misguided attempt to reduce causation to probability. But causation leaves a dist...
In this paper we show that the application of Oc-cam’s razor to the theory of causal Bayes nets give...
Four theories proposing determinate relations of actual causation for Boolean networks are described...
Humans possess considerable causal knowledge about the world. For example, one might have beliefs ab...
Alexander Gebharter (2017b) has proposed to use Bayesian network (BN) causal discovery methods to i...
Titans like Bertrand Russell or Karl Pearson warned us to keep ourmathematical and statistical hands...
