Supermodeling: Consensus by Synchronization of Alternative Models

author: Gregory Duane, Macedonian Academy of Science and Arts
published: Nov. 8, 2011,   recorded: October 2011,   views: 4098


Related Open Educational Resources

Related content

Report a problem or upload files

If you have found a problem with this lecture or would like to send us extra material, articles, exercises, etc., please use our ticket system to describe your request and upload the data.
Enter your e-mail into the 'Cc' field, and we will keep you updated with your request's status.
Lecture popularity: You need to login to cast your vote.


Computational models of an ongoing objective process, as in weather forecasting, must continually assimilate new observational data as they run. Both "truth" and "model" are chaotic systems that thus synchronize through a limited exchange of information in one direction - a phenomenon that can be characterized as machine perception. A recent suggestion has been to envision the fusion of different models analogously, as 3-way synchronization of the different models with reality. This phenomenon may be useful for improving climate projection by combining a few different models that differ in regard to the magnitude of global warming and regional predictions. Several machine learning approaches have been proposed to train the connections linking corresponding variables in the different models. Stochastic approaches can avoid non-global local optima, but it seems likely that an intelligent "expert system" approach would improve the supermodel.

See Also:

Download slides icon Download slides: solomon_duane_supermodeling_01.pdf (2.2 MB)

Help icon Streaming Video Help

Link this page

Would you like to put a link to this lecture on your homepage?
Go ahead! Copy the HTML snippet !

Write your own review or comment:

make sure you have javascript enabled or clear this field: