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person
Legg Mason
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Academic collaboration |
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This document page discusses a formal definition for "Pragmatic General Intelligence" within the context of intelligent agents. It introduces mathematical definitions incorporating environments, goals, and distributions to quantify an agent's expected performance. The text also compares this concept to universal intelligence and references the algorithmic agent AIXI.
This document discusses the limitations of Legg and Hutter's model of intelligent agents when applied to real-world scenarios, particularly regarding the separation of reward mechanisms from cognition. The text argues that biological intelligence often involves self-defined goals rather than external rewards and proposes treating external rewards as a theoretical test framework rather than an architectural necessity. It contrasts this approach with IQ tests, suggesting that formal definitions of intelligence can be inferred from real-world behavior.
This document is page 136 of an academic text titled 'A Formal Model of Intelligent Agents.' It discusses theoretical Artificial Intelligence concepts, specifically 'Biased Universal Intelligence,' referencing researchers Legg and Hutter and the Solomonoff-Levin distribution. The page bears a 'HOUSE_OVERSIGHT_013052' stamp, indicating it was part of a document production for a congressional investigation, likely related to Jeffrey Epstein's connections to the scientific community, though Epstein himself is not mentioned on this specific page.
This document is page 111 of a technical academic text discussing Artificial General Intelligence (AGI), specifically the 'CogPrime' and 'OpenCog' architectures. It details memory types, cognitive processes, and 'cognitive synergy' within the Probabilistic Logic Networks (PLN) framework. While technical in nature, the document bears the Bates stamp 'HOUSE_OVERSIGHT_013027', indicating it was collected as evidence during a US House Oversight Committee investigation, likely related to Jeffrey Epstein's funding of or connections to scientific research and AI projects.
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