Epstein Secrets

el, Mark Waser, Randal Koene, Paul Rosenbloom, Zhongzhi Shi, Steve Omohundro, Bill Hibbard, Eray Ozkural, Brandon Rohrer, Ben Johnston, John Laird, Shane Legg, Selmer Brin&sjord, Anders Sandberg, Alexei Samsonovich, Wlodek Duch, and more • The inimitable "Artilect Warrior" Hugo de Gans, who (when he was w

urations that carry out sensorimotor and categorization tasks. The emergence of higher-level cognition from this approach seems rather unlikely. • Ben Kuipers and his colleagues INIK07, MKOS, NIKOalhave pursued an extremely innovative research program which combines qualitative reasoning and reinforcement

mathematical rigor. Perhaps the most carefully- wrought formalization of intelligence so far is the theory of "universal intelligence" presented by Shane Legg and Marcus Hater in ILI I0714, which draws on ideas from algorithmic information theory. Universal intelligence captures a certain aspect of the "i

r the various cognitively-relevant properties of the environment from looking at data about the ev- eryday world. We agree in principle, and in fact Ben Kuipers and his colleagues have done some interesting work in this direction, showing that learning algorithms can infer some basics about the structure of

Arel, Mark Waser, Randal Koene, Paul Rosenbloom, Zhongzhi Shi, Steve Omohundro, Bill Hibbard, Eray Ozkural, Brandon Rohrer, Ben Johnston, John Laird, Shane Legg, Selmer Bringsjord, Anders Sandberg, Alexei Samsonovich, Wlodek Duch, and more The inimitable "Artilect Warrior" Hugo de Garis, who (when he was wor

igurations that carry out sensorimotor and categorization tasks. The emergence of higher-level cognition from this approach seems rather unlikely. e Ben Kuipers and his colleagues [MK07, MIX08, MIXO09]have pursued an extremely innovative research program which combines qualitative reasoning and reinforcement

f mathematical rigor. Perhaps the most carefully- wrought formalization of intelligence so far is the theory of “universal intelligence” presented by Shane Legg and Marcus Hutter in [LI07b], which draws on ideas from algorithmic information theory. Universal intelligence captures a certain aspect of the “int

er the various cognitively-relevant properties of the environment from looking at data about the ev- eryday world. We agree in principle, and in fact Ben Kuipers and his colleagues have done some interesting work in this direction, showing that learning algorithms can infer some basics about the structure of s