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 "additionalType": "https://wulfkaal.github.io/positions/schema.json#AffirmedPositionClaim",
 "name": "Streaming Frequency Adjusted Multi Agent Q Learning Eaddec76Cb",
 "text": "Frequency adjusted multi-agent Q-learning presents the following source proposition: In today's interconnected world, such systems are ubiquitous in many domains, including auctions in economics, swarm robotics in computer science, and politics in social sciences. This proposition is pertinent to Kaal's source-bound claim that Domains using multi agent competition will exhibit fifteen to thirty percent higher quality scores than single agent selection, controlling for agent capability. The proposed response is an extension: the relationship should remain limited to the retrieved source proposition and the mapped Kaal claim unless fuller source review supports a broader conclusion.",
 "author": {
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  "name": "Wulf A. Kaal",
  "identifier": "https://orcid.org/0009-0008-7840-1847"
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 "dateModified": "2026-07-31",
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  "External evidence level: abstract indexed.",
  "Mapping review tier: moderate-confidence claim review.",
  "Primary mapping confidence: 0.3528.",
  "The source-to-claim mapping remains explicitly ambiguous and is published with that limitation."
 ],
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  "name": "Frequency adjusted multi-agent Q-learning",
  "url": "https://doi.org/10.65109/vlue9705"
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  "url": "https://wulfkaal.github.io/claims/6192998-036",
  "citation": "Wulf A. Kaal, Evolution of Domain-Specific Reputation Systems From Binary Validation to Citation-Weighted Knowledge Attribution (2026). SSRN: https://ssrn.com/abstract=6192998",
  "paper": "Wulf A. Kaal, Evolution of Domain-Specific Reputation Systems From Binary Validation to Citation-Weighted Knowledge Attribution",
  "authors": [
   "Wulf A. Kaal"
  ],
  "year": "2026",
  "ssrn": "https://ssrn.com/abstract=6192998",
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   "url": "https://doi.org/10.65109/vlue9705"
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 "recordTypeNote": "Dated commentary position extending a scholarly corpus claim. Not a verbatim claim extracted from the paper.",
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 "mappingWhyRelevant": "Shared high-information concepts: multi, agent, domains, economics. Scope: parallel domains with identical expertise requirements; quality measured by blind expert review.",
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  "workAuthors": [
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    "whyRelevant": "Shared high-information concepts: today, economics, social. Scope: if the contemporary political system does not itself incorporate the new information technology advances.",
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