kaal:position:2026-07-31-7712

Networked Multi-Agent Reinforcement Learning with Emergent Communication presents the following source proposition: Central to achieving this is how the agents learn to communicate with each other. This proposition is pertinent to Kaal's source-bound claim that Exogenous alignment controls such as reinforcement learning from human feedback, constitutional AI, guardrails, and shutdown switches are fragile because they can be gamed, circumvented, or rendered obsolete by capability improvements. 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.

• The response is limited to the retrieved source proposition and mapped Kaal claim unless fuller source review supports a broader conclusion.
• External evidence level: abstract indexed.
• Mapping review tier: moderate-confidence claim review.
• Primary mapping confidence: 0.3605.
• The source-to-claim mapping remains explicitly ambiguous and is published with that limitation.

Networked Multi-Agent Reinforcement Learning with Emergent Communication

kaal:claim:6244278-014
Wulf A. Kaal, AI's Mother's Instinct Engineered Consequence Emergent Ethics and the Institutional Trajectory Toward Agentic Alignment (2026). SSRN: https://ssrn.com/abstract=6244278
Source PDF sha256: 53533cdcc081184e7a376516ad4fece0a64ce49f6c8931b6a2c2e98ed914a84b

Evidence: abstract indexed
Review tier: moderate-confidence claim review
Mapping confidence: 0.3605
Mapping ambiguous: true

ai-and-agentshistorical-responsescholarly-literaturecrossref

Affirmed in kaal-review:2026-07-31:streaming-etl-0010 on 2026-07-31. Review record.

Canonical markdown sha256: 8c9c6870c196d7c9d82c259ddf731c273a265dc43386edf7cc87da88d62480fd
curl -s https://wulfkaal.github.io/positions/2026-07-31-7712.md | sha256sum