In this paper we present a new approach to reason about actions and causation which is based on a conditional logic. The conditional implication is interpreted as causal implicati...
Causal reasoning is primarily concerned with what would happen to a system under external interventions. In particular, we are often interested in predicting the probability distr...
The causal Markov condition (CMC) is a postulate that links observations to causality. It describes the conditional independences among the observations that are entailed by a cau...
Bastian Steudel, Dominik Janzing, Bernhard Sch&oum...
We used a new method to assess how people can infer unobserved causal structure from patterns of observed events. Participants were taught to draw causal graphs, and then shown a ...
Tamar Kushnir, Alison Gopnik, Chris Lucas, Laura S...
Learning to understand a single causal system can be an achievement, but humans must learn about multiple causal systems over the course of a lifetime. We present a hierarchical B...
Charles Kemp, Noah D. Goodman, Joshua B. Tenenbaum
Many statistical methods have been proposed to estimate causal models in classical situations with fewer variables than observations. However, modern datasets including gene expres...
1 describe an approach to the problem of forming hypotheses about hidden mechanisms w; thin devices — the "black box" problem for physical systems. The approach involv...
Reasoning about causality is an interesting application area of formal nonmonotonic theories. Here we focus our attention on a certain aspect of causal reasoning, namely causaZ as...
models require the identi cation of abstractions and approximations that are well suited to the task at hand. In this paper we analyze the problem of automatically selecting adequ...