Optimal models of decision-making in dynamic environments.
Curr Opin Neurobiol
; 58: 54-60, 2019 10.
Article
em En
| MEDLINE
| ID: mdl-31326724
ABSTRACT
Nature is in constant flux, so animals must account for changes in their environment when making decisions. How animals learn the timescale of such changes and adapt their decision strategies accordingly is not well understood. Recent psychophysical experiments have shown humans and other animals can achieve near-optimal performance at two alternative forced choice (2AFC) tasks in dynamically changing environments. Characterization of performance requires the derivation and analysis of computational models of optimal decision-making policies on such tasks. We review recent theoretical work in this area, and discuss how models compare with subjects' behavior in tasks where the correct choice or evidence quality changes in dynamic, but predictable, ways.
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Tomada de Decisões
/
Aprendizagem
Tipo de estudo:
Prognostic_studies
Limite:
Animals
/
Humans
Idioma:
En
Revista:
Curr Opin Neurobiol
Assunto da revista:
BIOLOGIA
/
NEUROLOGIA
Ano de publicação:
2019
Tipo de documento:
Article