Back to search

Article

Empowerment Gain and Causal Model Construction: Children and adults are sensitive to controllability and variability in their causal interventions

2025-06-12

Abstract excerpt

<p>Learning about the causal structure of the world is a fundamental problem for human cognition. Causal models and especially causal learning have proved to be difficult for Large Models using standard techniques of deep learning. In contrast, cognitive scientists have applied advances in our formal understanding of causation in computer science, particularly within the Causal Bayes Net formalism, to understand h...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work
2cceba6b-1034-59e9-ad97-0d09a073786f
DOI
10.31234/osf.io/ept4n_v1
Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest
Interactive article relationship graphSelect a related publication card to move it into the centre and load its closest explainable connections. Solid lines are source-backed structured connections. Dashed lines are semantic discovery signals and are not scientific evidence.
Empowerment Gain and Causal Model Construction: Children and adults are sensitive to controllability and variability in their causal interventionsDOI 10.31234/osf.io/ept4n_v1
Select a neighboring publication to make it the new centre.