Computer Science Building, Room 151
I argue that data becomes temporarily interesting by itself to some self-improving, but computationally limited, subjective observer once he learns to predict or compress the data in a better way, thus making it subjectively simpler and more `beautiful.' Curiosity is the desire to create or discover more non-random, non-arbitrary, regular data that is novel and surprising not in the traditional sense of Boltzmann and Shannon but in the sense that it allows for compression progress because its regularity was not yet known. This drive maximizes interestingness, the first derivative of subjective beauty or compressibility, that is, the steepness of the learning curve. It motivates exploring infants, pure mathematicians, composers, artists, dancers, comedians, yourself, and recent artificial systems.
Based on keynote for KES 2008 and joint invited lecture for ALT 2007 / DS 2007; variants to appear in SICE Journal & Proc. ABIALS.
Professor of Artificial Intelligence at the University of Lugano, Switzerland: April 2009
Professor of Cognitive Robotics and Computer Science at TU Munich, Germany, since 2004
Professor SUPSI in Manno, Switzerland, since January 2003
Codirector of the Swiss AI Lab IDSIA, Lugano, Switzerland, since March 1995
Host: Andrew Barto