Distributed Learning in Hierarchical Networks
In this article, we propose distributed learning based approaches to study the evolution of a decentralized hierarchical system, an illustration of which is the smart grid. Smart grid management requires the control of non-renewable energy production and the inegration of renewable energies which might be highly unpredictable. Indeed, their production levels rely on uncontrolable factors such as sunshine, wind strength, etc. First, we derive optimal control strategies on the non-renewable energy productions and compare competitive learning algorithms to forecast the energy needs of the end users. Second, we introduce an online learning algorithm based on regret minimization enabling the agents to forecast the production of renewable energies. Additionally, we define organizations of the market promoting collaborative learning which generate higher performance for the whole smart grid than full competition.
|Date of creation:||09 Oct 2012|
|Date of revision:|
|Publication status:||Published in ValueTools 2012, Oct 2012, Cargèse, France. http://valuetools.org/2012/show/home, 2012|
|Note:||View the original document on HAL open archive server: https://hal.archives-ouvertes.fr/hal-00740905|
|Contact details of provider:|| Web page: https://hal.archives-ouvertes.fr/|
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Drew Fudenberg & David K. Levine, 1996.
"The Theory of Learning in Games,"
Levine's Working Paper Archive
624, David K. Levine.
- Young, H. Peyton, 2009. "Learning by trial and error," Games and Economic Behavior, Elsevier, vol. 65(2), pages 626-643, March.
- Fudenberg, Drew & Levine, David, 1998.
"Learning in games,"
European Economic Review,
Elsevier, vol. 42(3-5), pages 631-639, May.
When requesting a correction, please mention this item's handle: RePEc:hal:journl:hal-00740905. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (CCSD)
If references are entirely missing, you can add them using this form.