B. F. Skinner
PersonRelationship Network
Event Timeline
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Pavlov
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John Watson
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John Watson
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Academic scientific |
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| Date | Event Type | Description | Location | Actions |
|---|---|---|---|---|
| 1950-01-01 | N/A | B.F. Skinner programmed pigeons to perform elaborate actions using reinforcement learning. | Unknown | View |
| 1950-01-01 | N/A | B.F. Skinner programmed pigeons to perform elaborate actions including guiding missiles. | Unknown | View |
EFTA00024847.pdf
This document is an FBI Chain of Custody and Evidence Inventory log for Case 31E-MM-108062, item 1B5. It lists the contents of a box collected in 2006, which includes message printouts and expenditure records originating from the Palm Beach Police Department (PBPD) circa 2005, labeled with various initials (e.g., C.W., S.B., M.M.H.). The custody logs track the evidence from 2006 through a transfer to the New York field office in June 2019, shortly before Jeffrey Epstein's arrest, with a final inventory check in July 2021.
HOUSE_OVERSIGHT_016957.jpg
This document is page 154 of a book or article discussing the history and mechanics of Artificial Intelligence, specifically focusing on 'Bottom-up Deep Learning' and 'Reinforcement Learning.' It traces the history from B.F. Skinner's work in the 1950s to modern applications by Google's DeepMind (such as AlphaZero). While the document bears a 'HOUSE_OVERSIGHT' Bates stamp, suggesting it was part of a document production (potentially related to Jeffrey Epstein's scientific interests or funding), the text itself is purely scientific/academic and contains no direct reference to Epstein or his associates.
HOUSE_OVERSIGHT_016956.jpg
This document appears to be page 153 of a book or academic essay discussing cognitive science and learning theories. It contrasts 'bottom-up' learning (associated with behavioral psychologists like Skinner and machine learning) with 'top-down' learning (associated with Plato, Descartes, and Chomsky). The author uses the example of detecting email spam—specifically distinguishing between obvious 'Nigerian' scams and more subtle predatory journal solicitations—to illustrate how prior abstract knowledge helps in pattern recognition.
HOUSE_OVERSIGHT_016374.jpg
This document discusses the history and mechanics of AI learning methods, specifically focusing on "bottom-up deep learning" and "reinforcement learning." It references historical figures like B.F. Skinner and modern achievements by Google's DeepMind, such as AlphaZero and Atari game playing, to illustrate how computers detect patterns and learn through reward systems.
HOUSE_OVERSIGHT_016373.jpg
The text discusses the philosophical and psychological debate between bottom-up learning (association and pattern detection) and top-down learning (using abstract concepts and hypotheses). It illustrates these concepts using the analogy of filtering spam emails, contrasting machine learning pattern recognition with human reasoning based on background knowledge.
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