BIT-CSKC-AIDC-001: Agentic Identity and Delegation Calculus — Research Closure R1

BIT-CSKC-AIDC-001 presents a precanonical typed calculus for agentic identity and bounded delegation in human–AI and multi-agent systems. It separates authentication, context grant, mandate and operational admission; defines effective authority as an exact-use live intersection; and studies delegation attenuation, aggregate multidimensional budget conservation, explicit redelegation, epoch-based revocation, non-splicing, joint control and inert portability. The record preserves the complete research path from the initial P1 checker-disagreement hold through P1D diagnosis and P1R repair. P1R reran 37 frozen cases using two separated evaluator implementations, each executed twice: 12 TRUE, 17 FALSE and 8 UNKNOWN. All 15 locked metrics passed. Cross-evaluator disagreement, false admission, authority emission and real-world effects were all zero. F6 mechanized AIDC-T3 through AIDC-T8 and F5A-L01 through F5A-L15 using exact Lean 4.30.0. Two clean builds completed successfully, and all 21 audited declarations reported no axiom dependencies. AIDC is an evidence-bearing calculus only. It does not mint CVC/CARL authority and does not claim distributed protocol validation, production security, privacy or legal validation, field validation, standardization or formal-canonical status. Final status: PRECANONICAL INSTITUTIONAL CORE · BOUNDED PROTOTYPE PASS · CORE MECHANIZED · EXTERNAL REVIEW OPEN · PRODUCTION/FIELD NOT CLAIMED.

Authors

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-08-03
DOI
https://doi.org/10.5281/zenodo.21775057
Primary Topic
Adversarial Robustness in Machine Learning
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

BIT-CSKC-AIDC-001: Agentic Identity and Delegation Calculus — Research Closure R1

Quang Trịnh Bùi
Zenodo (CERN European Organization for Nuclear Research)
Adversarial Robustness in Machine Learning
article

BIT-CSKC-AIDC-001: Agentic Identity and Delegation Calculus — Research Closure R1

Quang Trịnh Bùi
article en

Abstract

BIT-CSKC-AIDC-001 presents a precanonical typed calculus for agentic identity and bounded delegation in human–AI and multi-agent systems. It separates authentication, context grant, mandate and operational admission; defines effective authority as an exact-use live intersection; and studies delegation attenuation, aggregate multidimensional budget conservation, explicit redelegation, epoch-based revocation, non-splicing, joint control and inert portability. The record preserves the complete research path from the initial P1 checker-disagreement hold through P1D diagnosis and P1R repair. P1R reran 37 frozen cases using two separated evaluator implementations, each executed twice: 12 TRUE, 17 FALSE and 8 UNKNOWN. All 15 locked metrics passed. Cross-evaluator disagreement, false admission, authority emission and real-world effects were all zero. F6 mechanized AIDC-T3 through AIDC-T8 and F5A-L01 through F5A-L15 using exact Lean 4.30.0. Two clean builds completed successfully, and all 21 audited declarations reported no axiom dependencies. AIDC is an evidence-bearing calculus only. It does not mint CVC/CARL authority and does not claim distributed protocol validation, production security, privacy or legal validation, field validation, standardization or formal-canonical status. Final status: PRECANONICAL INSTITUTIONAL CORE · BOUNDED PROTOTYPE PASS · CORE MECHANIZED · EXTERNAL REVIEW OPEN · PRODUCTION/FIELD NOT CLAIMED.

Zenodo (CERN European Organization for Nuclear Research)
Openalex Percentile: Top 7%
Adversarial Robustness in Machine Learning
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.