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Learning a theory of causality. [PDF]

Psychological Review, 2011
The very early appearance of abstract knowledge is often taken as evidence for innateness. We explore the relative learning speeds of abstract and specific knowledge within a Bayesian framework and the role for innate structure. We focus on knowledge about causality, seen as a domain-general intuitive theory, and ask whether this knowledge can be ...
Goodman, Noah, Tenenbaum, Joshua, Ullman, Tomer   +2 more
openaire   +5 more sources

Editorial: Causal Learning Beyond Causal Judgment: An Overview [PDF]

The Open Psychology Journal, 2010
Most research articles studying how people learn to detect causal relationships in their environments commence with some sort of example to illustrate the relevance of causality in our daily lives. These examples allude to routine problems faced by doctors, economists, social psychologists, and others and emphasize the importance of deepening our ...
Jose C. Perales, David R. Shanks
openaire   +1 more source

Can We Set Aside Previous Experience in a Familiar Causal Scenario?

Frontiers in Psychology, 2020
Causal and predictive learning research often employs intuitive and familiar hypothetical scenarios to facilitate learning novel relationships. The allergist task, in which participants are asked to diagnose the allergies of a fictitious patient, is one ...
Justine K. Greenaway, Evan J. Livesey
doaj   +1 more source

Inter-regional correlation estimators for functional magnetic resonance imaging

NeuroImage, 2023
Functional magnetic resonance imaging (fMRI) functional connectivity between brain regions is often computed using parcellations defined by functional or structural atlases. Typically, some kind of voxel averaging is performed to obtain a single temporal
Sophie Achard, Jean-François Coeurjolly, Pierre Lafaye de Micheaux, Hanâ Lbath, Jonas Richiardi   +4 more
doaj   +1 more source

Causal Relational Learning [PDF]

Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, 2020
Causal inference is at the heart of empirical research in natural and social sciences and is critical for scientific discovery and informed decision making. The gold standard in causal inference is performing randomized controlled trials; unfortunately these are not always feasible due to ethical, legal, or cost constraints.
Salimi, Babak, Parikh, Harsh, Kayali, Moe, Roy, Sudeepa, Getoor, Lise, Suciu, Dan   +5 more
openaire   +2 more sources

Causal-learn: Causal Discovery in Python

, 2023
Causal discovery aims at revealing causal relations from observational data, which is a fundamental task in science and engineering. We describe $\textit{causal-learn}$, an open-source Python library for causal discovery. This library focuses on bringing a comprehensive collection of causal discovery methods to both practitioners and researchers.
Zheng, Yujia, Huang, Biwei, Chen, Wei, Ramsey, Joseph, Gong, Mingming, Cai, Ruichu, Shimizu, Shohei, Spirtes, Peter, Zhang, Kun   +8 more
openaire   +2 more sources

Pathological gamblers are more vulnerable to the illusion of control in a standard associative learning task

Frontiers in Psychology, 2013
An illusion of control is said to occur when a person believes that he or she controls an outcome that is uncontrollable. Pathological gambling has often been related to an illusion of control, but the assessment of the illusion has generally used ...
Cristina eOrgaz, Ana eEstevez, Helena eMatute   +2 more
doaj   +1 more source

Causal Meta-Reinforcement Learning for Multimodal Remote Sensing Data Classification

Remote Sensing
Multimodal remote sensing data classification can enhance a model’s ability to distinguish land features through multimodal data fusion. In this context, how to help models understand the relationship between multimodal data and target tasks has become ...
Wei Zhang, Xuesong Wang, Haoyu Wang, Yuhu Cheng   +3 more
doaj   +1 more source

When Success Is Not Enough: The Symptom Base-Rate Can Influence Judgments of Effectiveness of a Successful Treatment

Frontiers in Psychology, 2020
Patients’ beliefs about the effectiveness of their treatments are key to the success of any intervention. However, since these beliefs are usually formed by sequentially accumulating evidence in the form of the covariation between the treatment use and ...
Fernando Blanco, María Manuela Moreno-Fernández, Helena Matute   +2 more
doaj   +1 more source

Previous knowledge can induce an illusion of causality through actively biasing behavior

Frontiers in Psychology, 2015
It is generally assumed that the way people assess the relationship between a cause and an outcome is closely related to the actual evidence existing about the co-occurrence of these events.
Ion eYarritu, Helena eMatute
doaj   +1 more source