APR-Lite Phases 7.1–7.3 Technical Note: Coalition Learning, Mesh Topology, and Governance Hardening in Regulated Multi-Agent AI Systems

This technical note describes Phases 7.1, 7.2, and 7.3 of the APR-Lite governance platform, completing the 7.x governance line. Phase 7.1 introduces Coalition Learning — a governed mechanism for proposing, reviewing, activating, and rolling back changes to coalition behavior under strict two-person rule and evidence requirements. Phase 7.2 introduces Mesh Topology and Learning Governance — directed acyclic graph routing with cycle detection, fan-out and fan-in ceilings, and change-set schema validation at proposal time. Phase 7.3 is a governance hardening pass that introduces unified governance event envelopes, deterministic evaluator ordering, total freeze semantics, tenant config integrity validation, and mesh safety case evaluation. Together these three phases complete a fully governed, multi-tenant, multi-agent substrate with coalition drift, cross-session drift, mesh routing, rollback governance, learning ceilings, two-person rule, tenant ceilings, freeze semantics, and unified evaluator ordering. The implementation is validated against a 28-test smoke suite.

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-03-24
DOI
https://doi.org/10.5281/zenodo.19209396
Primary Topic
Reinforcement Learning in Robotics
Type
article
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article

APR-Lite Phases 7.1–7.3 Technical Note: Coalition Learning, Mesh Topology, and Governance Hardening in Regulated Multi-Agent AI Systems

Zenodo (CERN European Organization for Nuclear Research)
Reinforcement Learning in Robotics
article

APR-Lite Phases 7.1–7.3 Technical Note: Coalition Learning, Mesh Topology, and Governance Hardening in Regulated Multi-Agent AI Systems

article en

Abstract

This technical note describes Phases 7.1, 7.2, and 7.3 of the APR-Lite governance platform, completing the 7.x governance line. Phase 7.1 introduces Coalition Learning — a governed mechanism for proposing, reviewing, activating, and rolling back changes to coalition behavior under strict two-person rule and evidence requirements. Phase 7.2 introduces Mesh Topology and Learning Governance — directed acyclic graph routing with cycle detection, fan-out and fan-in ceilings, and change-set schema validation at proposal time. Phase 7.3 is a governance hardening pass that introduces unified governance event envelopes, deterministic evaluator ordering, total freeze semantics, tenant config integrity validation, and mesh safety case evaluation. Together these three phases complete a fully governed, multi-tenant, multi-agent substrate with coalition drift, cross-session drift, mesh routing, rollback governance, learning ceilings, two-person rule, tenant ceilings, freeze semantics, and unified evaluator ordering. The implementation is validated against a 28-test smoke suite.

Zenodo (CERN European Organization for Nuclear Research)
Peace, Justice and strong institutions
Openalex Percentile: Top 12%
Reinforcement Learning in Robotics
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