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Learning the value of information and reward over time when solving exploration-exploitation problems

Irene Cogliati Dezza, Angela J. Yu, Axel Cleeremans and William Alexander UGent (2017) SCIENTIFIC REPORTS. 7.
abstract
To flexibly adapt to the demands of their environment, animals are constantly exposed to the conflict resulting from having to choose between predictably rewarding familiar options (exploitation) and risky novel options, the value of which essentially consists of obtaining new information about the space of possible rewards (exploration). Despite extensive research, the mechanisms that subtend the manner in which animals solve this exploitation-exploration dilemma are still poorly understood. Here, we investigate human decision-making in a gambling task in which the informational value of each trial and the reward potential were separately manipulated. To better characterize the mechanisms that underlined the observed behavioural choices, we introduce a computational model that augments the standard reward-based reinforcement learning formulation by associating a value to information. We find that both reward and information gained during learning influence the balance between exploitation and exploration, and that this influence was dependent on the reward context. Our results shed light on the mechanisms that underpin decision-making under uncertainty, and suggest new approaches for investigating the exploration-exploitation dilemma throughout the animal kingdom.
Please use this url to cite or link to this publication:
author
organization
year
type
journalArticle (original)
publication status
published
keyword
DECISION-MAKING, UNCERTAINTY, HUMANS, BRAIN, MODEL, RISK
journal title
SCIENTIFIC REPORTS
Sci Rep
volume
7
article number
16919
pages
13 pages
publisher
Nature Publishing Group
place of publication
London
Web of Science type
Article
Web of Science id
000417050200009
ISSN
2045-2322
DOI
10.1038/s41598-017-17237-w
language
English
UGent publication?
yes
classification
A1
id
8552704
handle
http://hdl.handle.net/1854/LU-8552704
date created
2018-03-01 15:06:03
date last changed
2018-05-15 13:00:31
@article{8552704,
  abstract     = {To flexibly adapt to the demands of their environment, animals are constantly exposed to the conflict resulting from having to choose between predictably rewarding familiar options (exploitation) and risky novel options, the value of which essentially consists of obtaining new information about the space of possible rewards (exploration). Despite extensive research, the mechanisms that subtend the manner in which animals solve this exploitation-exploration dilemma are still poorly understood. Here, we investigate human decision-making in a gambling task in which the informational value of each trial and the reward potential were separately manipulated. To better characterize the mechanisms that underlined the observed behavioural choices, we introduce a computational model that augments the standard reward-based reinforcement learning formulation by associating a value to information. We find that both reward and information gained during learning influence the balance between exploitation and exploration, and that this influence was dependent on the reward context. Our results shed light on the mechanisms that underpin decision-making under uncertainty, and suggest new approaches for investigating the exploration-exploitation dilemma throughout the animal kingdom.},
  articleno    = {16919},
  author       = {Dezza, Irene Cogliati and Yu, Angela J. and Cleeremans, Axel and Alexander, William},
  issn         = {2045-2322},
  journal      = {SCIENTIFIC REPORTS},
  keyword      = {DECISION-MAKING,UNCERTAINTY,HUMANS,BRAIN,MODEL,RISK},
  language     = {eng},
  pages        = {13},
  publisher    = {Nature Publishing Group},
  title        = {Learning the value of information and reward over time when solving exploration-exploitation problems},
  url          = {http://dx.doi.org/10.1038/s41598-017-17237-w},
  volume       = {7},
  year         = {2017},
}

Chicago
Dezza, Irene Cogliati, Angela J. Yu, Axel Cleeremans, and William Alexander. 2017. “Learning the Value of Information and Reward over Time When Solving Exploration-exploitation Problems.” Scientific Reports 7.
APA
Dezza, I. C., Yu, A. J., Cleeremans, A., & Alexander, W. (2017). Learning the value of information and reward over time when solving exploration-exploitation problems. SCIENTIFIC REPORTS, 7.
Vancouver
1.
Dezza IC, Yu AJ, Cleeremans A, Alexander W. Learning the value of information and reward over time when solving exploration-exploitation problems. SCIENTIFIC REPORTS. London: Nature Publishing Group; 2017;7.
MLA
Dezza, Irene Cogliati, Angela J. Yu, Axel Cleeremans, et al. “Learning the Value of Information and Reward over Time When Solving Exploration-exploitation Problems.” SCIENTIFIC REPORTS 7 (2017): n. pag. Print.