CACrown ArchivesThe cinema collection
Menu
Research dossier · General Reference

Stochastic Neural Analog Reinforcement Calculator

neural-net machine

Cross-disciplinary reference desk with index cards, atlas, dictionary and catalogue
General referenceInterpretive dossier study · Crown Archives visual atlas
Record originEnglish Wikipedia
Text licenseCC BY-SA 4.0
Source revisionAug 4, 2026
Entity authorityQ7617823 ↗
Source-derived summary

The Stochastic Neural Analog Reinforcement Calculator (SNARC) is a neural network machine designed by Marvin Minsky. Prompted by a letter from Minsky, George Armitage Miller gathered the funding (a few thousand dollars) for the project from the Office of Naval Research of the U.S. Department of Defense in the summer of 1951 with the work to be carried out by Minsky, who was then a graduate student in mathematics at Princeton University. At the time, a physics graduate student at Princeton, Dean S. Edmonds, volunteered that he was good with electronics and therefore Minsky brought him onto the project.

During undergraduate years, Minsky was inspired by the 1943 Warren McCulloch and Walter Pitts paper on artificial neurons, and decided to build such a machine. The learning was Skinnerian reinforcement learning, and Minsky talked with Skinner extensively during the development of the machine. They tested the machine on a copy of Shannon's maze, and found that it could learn to solve the maze. Unlike Shannon's maze, this machine did not control a physical robot, but simulated rats running in a maze. The simulation is displayed as an "arrangement of lights", and the circuit was reinforced each time the simulated rat reached the goal.

The machine surprised its creators. "The rats actually interacted with one another.

Editorial summary

This brief starts where responsible research should: with the source description of “Stochastic Neural Analog Reinforcement Calculator” as neural-net machine. Everything that follows is an evidence route, not borrowed authority.

Editorial reviewA concise reference frame for defining the subject, testing terminology and identifying the institution closest to the evidence. The current lead gives the account dated anchors—1951, 1943—that can be checked directly. The selected authority fields contribute no independent date. The account is most persuasive where Stochastic, Neural and Analog can be independently traced.
Editorial analysis

Why this record matters

The subject matters to the general reference register because the source frames it as neural-net machine. Its deeper value depends on whether names, dates, institutions and citations support that framing.

Evidence profile

Vocabulary and entity names are the principal evidence signals here, because they determine the precision of every later search. The source revision retrieved here is dated Aug 4, 2026. The linked authority identifier is Q7617823. None of the 0 selected statements returned an explicit reference. The first chronological checks are 1951 and 1943.

Critical limits

Overview language is designed for orientation and should not be treated as a substitute for the evidence cited beneath it. The lead is largely declarative, so disagreement and counter-evidence require a deliberate search beyond the opening account. Authority statements aid reconciliation but still require their own references, qualifiers and ranks to be checked.

How to read it

Use the entry as an orientation point, then follow its citations and revision history. Names, dates and institutional relationships should be checked against the original record.

Best used for
  • Subject orientation
  • Search vocabulary
  • Locating named sources
Verify next

The closest primary source, responsible institution and strongest cited specialist reference.

Three-step research path

  1. Establish the record: confirm the title “Stochastic Neural Analog Reinforcement Calculator”, its source revision and the description used here.
  2. Expand the search: follow Stochastic Neural Analog Reinforcement Calculator primary sources, Stochastic Neural Analog Reinforcement Calculator archive and Stochastic research across catalogues and specialist indexes.
  3. Test the account: compare the strongest cited source with the responsible institution’s current record and note any disagreement.

Questions for further research

  1. Which source most directly establishes the central claim about “Stochastic Neural Analog Reinforcement Calculator”?
  2. Which institution is responsible for the underlying evidence?
  3. Which cited source is closest to the event, object or claim?
Subject index

Search terms from this dossier

Source & attribution

This entry incorporates text from “Stochastic Neural Analog Reinforcement Calculator” on English Wikipedia. Contributors are listed in the page history. Text is available under the Creative Commons Attribution-ShareAlike 4.0 License. Selected authority identifiers and statements are retrieved from Wikidata under CC0; their references and qualifiers remain part of the verification path.