kaal:position:2026-07-31-7739

Agent reasoning for norm compliance: a semantic approach presents the following source proposition: Assuming that which norms will have to be followed is unknown at design time, it is not possible to pre-program agents such that their behavior is norm compliant. This proposition is pertinent to Kaal's source-bound claim that Taken together, the transparency, decentralized decision making, and automated real time response properties of the proposed model make decentralized governance superior to AI driven supervision for secure, compliant, and efficient execution of AI agent transactions. 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: 0.4659.
• The source-to-claim mapping remains explicitly ambiguous and is published with that limitation.

Agent reasoning for norm compliance: a semantic approach

kaal:claim:5245185-039
Wulf A. Kaal, How can we Best Monitor AI Agents (2025). SSRN: https://ssrn.com/abstract=5245185
Source PDF sha256: 4d7adba83ec722480e97bde6528cbe9ce98c709e45cb18794f157a64b8fe7da2

Evidence: abstract indexed
Review tier: moderate-confidence claim review
Mapping confidence: 0.4659
Mapping ambiguous: true

decentralizationgovernance-designai-and-agentscompliancehistorical-responsescholarly-literaturecrossref

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

Canonical markdown sha256: fdd3fa624b4439efa0ec729fdb2800e38c33ed2bac51fa56e4ead8910e25e7b7
curl -s https://wulfkaal.github.io/positions/2026-07-31-7739.md | sha256sum