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

ion and intelligence. It has been tested on some practical control applications, and also on simulating artificial agents in a simple virtual world. MicroPsi's comprehen- siveness and basis in neuroscience and psychology are impressive, but in the current version of MicroPsi, learning and reasoning are ca

nts in a simple virtual world. MicroPsi's comprehen- siveness and basis in neuroscience and psychology are impressive, but in the current version of MicroPsi, learning and reasoning are carried out by algorithms that seem unlikely to scale. OCP incorporates the Psi model for motivation and emotion, so tha

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

tion and intelligence. It has been tested on some practical control applications, and also on simulating artificial agents in a simple virtual world. MicroPsi’s comprehen- siveness and basis in neuroscience and psychology are impressive, but in the current version of MicroPsi, learning and reasoning are car

ents in a simple virtual world. MicroPsi’s comprehen- siveness and basis in neuroscience and psychology are impressive, but in the current version of MicroPsi, learning and reasoning are carried out by algorithms that seem unlikely to scale. OCP incorporates the Psi model for motivation and emotion, so that

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

ut on the big- picture level the main difference lies in the way the cognitive synergy principle is pursued in the two different approaches. Psi and MicroPsi rely on very simple learning algorithms that are closely tied to the "quad" neurosymbolic knowledge representation, and hence interoperate in a fai

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

but on the big- picture level the main difference lies in the way the cognitive synergy principle is pursued in the two different approaches. Psi and MicroPsi rely on very simple learning algorithms that are closely tied to the “quad” neurosymbolic knowledge representation, and hence interoperate in a fairl