Back to Search
Start Over
The computational challenge of social learning
- Source :
- Trends Cogn Sci
- Publication Year :
- 2021
- Publisher :
- Elsevier BV, 2021.
-
Abstract
- The complex reward structure of the social world and the uncertainty endemic to social contexts poses a challenge for modeling. For example, during social interactions, the actions of one person influence the internal states of another. These social dependencies make it difficult to formalize social learning problems in a mathematically tractable way. While it is tempting to dispense with these complexities, they are a defining feature of social life. Because the structure of social interactions challenges the simplifying assumptions often made in models, they make an ideal testbed for computational models of cognition. By adopting a framework that embeds existing social knowledge into the model, we can go beyond explaining behaviors in laboratory tasks to explaining those observed in the wild.
- Subjects :
- Structure (mathematical logic)
Computational model
Cognitive Neuroscience
Testbed
Uncertainty
Inference
Experimental and Cognitive Psychology
Cognition
Social learning
Data science
Social Learning
Article
Ideal (ethics)
Neuropsychology and Physiological Psychology
Reward
Feature (machine learning)
Humans
Learning
Psychology
Subjects
Details
- ISSN :
- 13646613
- Volume :
- 25
- Database :
- OpenAIRE
- Journal :
- Trends in Cognitive Sciences
- Accession number :
- edsair.doi.dedup.....f113442e79df29a8f5cbd4ba148db564
- Full Text :
- https://doi.org/10.1016/j.tics.2021.09.002