no code implementations • 12 Apr 2018 • Shawn L. E. Beaulieu, Sam Kriegman, Josh C. Bongard
Generally intelligent agents exhibit successful behavior across problems in several settings.
1 code implementation • 6 Apr 2018 • Sam Kriegman, Nick Cheney, Francesco Corucci, Josh C. Bongard
Typically, AI researchers and roboticists try to realize intelligent behavior in machines by tuning parameters of a predefined structure (body plan and/or neural network architecture) using evolutionary or learning algorithms.
no code implementations • 8 Sep 2017 • Mark D. Wagy, Josh C. Bongard, James P. Bagrow, Paul D. H. Hines
In order to test its potential for useful application in a Smart Grid context, this paper investigates the extent to which a crowd can contribute predictive hypotheses to a model of residential electric energy consumption.
1 code implementation • 24 Jun 2017 • Sam Kriegman, Marcin Szubert, Josh C. Bongard, Christian Skalka
Satellite imagery and remote sensing provide explanatory variables at relatively high resolutions for modeling geospatial phenomena, yet regional summaries are often desirable for analysis and actionable insight.
1 code implementation • 22 Jun 2017 • Sam Kriegman, Nick Cheney, Francesco Corucci, Josh C. Bongard
Different subsystems of organisms adapt over many time scales, such as rapid changes in the nervous system (learning), slower morphological and neurological change over the lifetime of the organism (postnatal development), and change over many generations (evolution).
no code implementations • 8 Sep 2015 • Nicholas Allgaier, Tobias Banaschewski, Gareth Barker, Arun L. W. Bokde, Josh C. Bongard, Uli Bromberg, Christian Büchel, Anna Cattrell, Patricia J. Conrod, Christopher M. Danforth, Sylvane Desrivières, Peter S. Dodds, Herta Flor, Vincent Frouin, Jürgen Gallinat, Penny Gowland, Andreas Heinz, Bernd Ittermann, Scott Mackey, Jean-Luc Martinot, Kevin Murphy, Frauke Nees, Dimitri Papadopoulos-Orfanos, Luise Poustka, Michael N. Smolka, Henrik Walter, Robert Whelan, Gunter Schumann, Hugh Garavan, IMAGEN Consortium
In the present study, we introduce just such a method, called nonlinear functional mapping (NFM), and demonstrate its application in the analysis of resting state fMRI from a 242-subject subset of the IMAGEN project, a European study of adolescents that includes longitudinal phenotypic, behavioral, genetic, and neuroimaging data.