Skip to content
RDL
Network
Ecosystem
Switch app
TR
About
FAQ
Sign in
Get started
Modeling the development of decision making in volatile environments using strategies, reinforcement learning, and Bayesian inference — Maria K. Eckstein (2019) | RDL Network
Back
Cite
Save
Save for later
Share
Home
Publications
Modeling the development of decision making in volatile environments using strategies, reinforcement learning, and Bayesian inference
Shared by
Ronald E Dahl
University of California, Berkeley
Modeling the development of decision making in volatile environments using strategies, reinforcement learning, and Bayesian inference
Article
2019
en
Authors
+2 more
ME
Maria K. Eckstein
SM
Sarah L. Master
Ronald E Dahl
University of California, Berkeley
Discussion
(0)
Sign in
to like and join the discussion.
No comments yet. Be the first to comment.
Related publications
Dataset
hBayesDM: Hierarchical Bayesian Modeling of Decision-Making Tasks
Woo‐Young Ahn
,
Nate Haines
,
Lei Zhang
Article
2010
Observing the Observer (I): Meta-Bayesian Models of Learning and Decision-Making
Jean Daunizeau
,
Hanneke E.M. den Ouden
,
Matthias Pessiglione
,
Stefan J. Kiebel
,
Klaas Ε. Stephan
,
Karl Friston
Preprint
2021
Scenic4RL: Programmatic Modeling and Generation of Reinforcement\n Learning Environments
Abdus Salam Azad
,
Edward Kim
,
Qiancheng Wu
,
Kimin Lee
,
Ion Stoica
,
Pieter Abbeel
,
Sanjit A. Seshia
Article
2008
Integrated Bayesian models of learning and decision making for saccadic eye movements
Kay H. Brodersen
,
W.D. Penny
,
Lee Harrison
,
Jean Daunizeau
,
Christian C. Ruff
,
Emrah Düzel
,
Karl Friston
,
Klaas Ε. Stephan
Preprint
2022
Reinforcement learning and Bayesian inference provide complementary models for the unique advantage of adolescents in stochastic reversal
Maria K. Eckstein
,
Sarah L. Master
,
Ronald E Dahl
,
Linda Wilbrecht
,
Anne Collins
Discussion(0)
No comments yet. Be the first to comment.