# Multi agent competition

`kaal:entity:multi-agent-competition`

**Status.** derived

This node is assembled mechanically from the 4 claims that carry the concept tag `multi-agent-competition`. It is a roster of what the corpus says under this term. It is **not** an adjudicated definition: no single statement here has been ruled canonical, and no first-appearance call has been made. Read the claims and judge for yourself.

## Every claim under this term

4 claims across 1 works, 2026 to 2026.

**2026**

- [6192998-019](https://wulfkaal.github.io/claims/6192998-019) [design/argued] -- Multi agent competitive collaboration captures a diversity dividend worth more than half a standard deviation of quality improvement while enabling attribution through citation graphs.
  > Our multi-agent competitive collaboration protocol captures diversity dividends worth 0.5+ standard deviations of quality improvement while enabling attribution through citation graphs.
  Wulf A. Kaal, Evolution of Domain-Specific Reputation Systems From Binary Validation to Citation-Weighted Knowledge Attribution (2026). SSRN: https://ssrn.com/abstract=6192998
- [6192998-020](https://wulfkaal.github.io/claims/6192998-020) [condition/argued] *(failure mode)* -- The real barrier to multi agent competition is not cost but the absence of an attribution mechanism: if only the best of several competing agents is paid, the others have no incentive to participate, so competition requires rewards proportional to each contributor's contribution.
  > The real barrier is the lack of attribution mechanism. If 5 agents compete but only the best gets paid, the other 4 have no incentive to participate. We need a framework where all contributors can be rewarded proportional to their contribution.
  Wulf A. Kaal, Evolution of Domain-Specific Reputation Systems From Binary Validation to Citation-Weighted Knowledge Attribution (2026). SSRN: https://ssrn.com/abstract=6192998
- [6192998-032](https://wulfkaal.github.io/claims/6192998-032) [mechanism/argued] -- Multi agent competition improves attack resistance because it creates multiple attack surfaces that must all succeed simultaneously, and citation transparency makes collusion detectable; with a fifty percent quality penalty for detected collusion the corruption cost doubles relative to the original framework.
  > This improved security stems from multi-agent competition creating multiple attack surfaces that must all succeed simultaneously, combined with citation transparency enabling collusion detection.
  Wulf A. Kaal, Evolution of Domain-Specific Reputation Systems From Binary Validation to Citation-Weighted Knowledge Attribution (2026). SSRN: https://ssrn.com/abstract=6192998
- [6192998-036](https://wulfkaal.github.io/claims/6192998-036) [predictive/speculative] -- Domains using multi agent competition will exhibit fifteen to thirty percent higher quality scores than single agent selection, controlling for agent capability.
  > Expertise domains using multi-agent competition will exhibit 15-30% higher quality scores compared to single-agent selection, controlling for agent capability.
  Wulf A. Kaal, Evolution of Domain-Specific Reputation Systems From Binary Validation to Citation-Weighted Knowledge Attribution (2026). SSRN: https://ssrn.com/abstract=6192998

## Verify

Every claim above resolves to a record carrying a verbatim source quote, the sha256 of the source PDF, and a preformatted citation. Nothing here asks to be taken on trust.

    curl -s https://wulfkaal.github.io/entities/multi-agent-competition.md | sha256sum

**Canonical form.** This markdown file is the canonical hashed representation of this entity node. Its sha256 is the content hash.