Epstein Secrets

ligence resulting from the the AGI Roaclmap Workshop held at the University of Knoxville in October 2008 r, which was organized by Ben Goertzel and Itamar Arel. In this list, each broad competency area is listed together with a number of specific competencies sub-areas within its scope: 1. Perception: visi

ake c to denote algorithmic information measured on some reference Turing machine, and F(X) to denote what appears on the second tape of a two-tape Turing machine t time-steps after placing X on its first tape. Other more naturalistic computational models are also possible here and are discussed extens

: Stan Franklin, Juergen Schmidhuber, Marcus Hutter, Kai-Uwe Kuehnberger, Stephen Reed, Blerim Enruli, Kristinn Thorisson, Joscha Bach, Abram Demski, Itamar Arel, Mark Waser, Randal Koene, Paul Rosenbloom, Zhongzhi Shi, Steve Omohundro, Bill Hibbard, Eray Ozkural, Brandon Rohrer, Ben Johnston, John Laird, Shan

take c to denote algorithmic information measured on some reference Turing machine, and F(X) to denote what appears on the second tape of a two-tape Turing machine ¢ time-steps after placing X on its first tape. Other more naturalistic computational models are also possible here and are discussed extensi

t control systems. e Deep learning networks as a model of perception (and action and reinforcement learning), as embodied for example in the work of Itamar Arel [ARC09] and Jeff Hawkins [HB06]. The integrative diagram adopts this as the basic model of the perception and action subsystems of human intelligence

already encompassed by Legg and Hutter’s definition because one may bias the distribution of environments within the latter by considering different Turing machines underlying the Kolmogorov complexity. However this is not a general equivalence because the Solomonoff-Levin measure intrinsically HOUSE_OV