Deconstructing the human algorithms for exploration

•Exploration algorithms can be distinguished in terms of the bias and slope of choice functions.•Two experiments show evidence for both directed and random exploration.•A hybrid algorithm provides the best quantitative model of the choice data. The dilemma between information gathering (exploration)...

Ausführliche Beschreibung

Gespeichert in:

Bibliographische Detailangaben
Veröffentlicht in:	Cognition Jg. 173; S. 34 - 42
1. Verfasser:	Gershman, Samuel J.
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Netherlands Elsevier B.V 01.04.2018 Elsevier Science Ltd
Schlagworte:	Algorithms Bayesian analysis Bayesian inference Bias Change agents Changes Cognition & reasoning Cognitive ability Cognitive psychology Computer applications Experiments Exploitation Exploration Explore-exploit dilemma Information gathering Learning Mathematical models Reinforcement Reinforcement learning Response bias Sampling Uncertainty Bayesian inference Explore-exploit dilemma Reinforcement learning
ISSN:	0010-0277, 1873-7838, 1873-7838
Online-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

Schreiben Sie den ersten Kommentar!