IDEAS home Printed from https://ideas.repec.org/h/spr/sptchp/978-981-10-6439-5_7.html
   My bibliography  Save this book chapter

Learning Theory and Experiments in Neuroeconomics

In: Behavioral Economics

Author

Listed:
  • Masao Ogaki

    (Keio University)

  • Saori C. Tanaka

    (ATR Brain Information Communication Research Laboratory Group)

Abstract

Learning is an important factor in decision making under a novel or unstable environment. Reinforcement learning theory is a promising framework as a computational model of the brain in the process of the decision making in humans and animals. The hypothesis of dopamineDopamine in learning signals has been established by a huge amount of experimental evidence in animal neurophysiology and human imaging studies. The quest for the detailed neural mechanism of decision making is the first step to develop an economic theory that can explain real human behavior including individual preference.

Suggested Citation

  • Masao Ogaki & Saori C. Tanaka, 2017. "Learning Theory and Experiments in Neuroeconomics," Springer Texts in Business and Economics, in: Behavioral Economics, chapter 0, pages 105-114, Springer.
    • Handle: RePEc:spr:sptchp:978-981-10-6439-5_7
    DOI: 10.1007/978-981-10-6439-5_7
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:sptchp:978-981-10-6439-5_7. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.