Purpose-aware AI agent benchmark: 72 synthetic scenarios, four reproducible baselines and inspectable permission traces. Python, offline.
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Updated
Sep 17, 2026 - HTML
Purpose-aware AI agent benchmark: 72 synthetic scenarios, four reproducible baselines and inspectable permission traces. Python, offline.
AI-agent black-box recorder for tamper-evident DIKWP traces, incident replay, provenance and audit.
DIKWP semantic-network prototype: 25 transformation classes, multi-observer conflicts and reproducible analysis. Python, offline.
Claim-to-evidence verification for AI answers and retrieval-augmented generation: provenance, unsupported-claim detection and reversible review.
Offline research studio for artificial-consciousness indicators, claim levels, evidence ledgers, scenarios and governance.
Offline functional white-box evaluation for LLMs across DIKWP transformations, inspectable artifacts, risks and boundaries.
Compile mathematical problems into deterministic, hash-linked, machine-readable audit certificates with explicit proof boundaries.
Yucong Duan's research hub: DIKWP graphs, artificial consciousness, semantic mathematics, auditable AI, publications and reproducible open-source experiments.
Offline continuity and autonomous-learning research system for K-12 education under uncertain AI futures, with rights, agency, resilience and reversible pathways.
Offline opportunity planning: funded demand, DIKWP capability maps, market saturation, competing scenarios and reviewable evidence receipts. Python + browser; synthetic research examples.
Evidence-scoped transparent economy lab: bounded opportunity tests, exact contribution accounting, scenario analysis and replayable receipts. Offline Python and browser tools.
Executable brain-history research companion: 18 chapter labs, reconstructive memory, evidence evaluation and purpose-pinned plans. Python, MIT.
Recomputable nervous-system research companion: 24 experiments, 18 chapter labs, evidence memory and replayable run capsules. Python, Apache-2.0.
Executable liver-history research companion: competing dynamic models, finite belief-state policies, physical ledgers, observation design, and traceable DIKWP experiment capsules. Python 3.10+, Apache-2.0.
Evidence and context auditing for AI: inspect incentives, appeals and agent lineage, then validate outputs. Python and offline HTML.
Purpose-conditioned vision, revisable evidence and 12 executable research laboratories for A Brief History of Vision. Python, local studio, reproducible benchmarks.
Energy-information kidney science workbench accompanying A Brief History of the Kidney: 24 experiments, 18 chapter labs, reproducible DIKWP records, and a dependency-free Python interface. Apache-2.0.
Buyer-committed demand, shared-capacity planning and signed outcome records. Python, SQLite and an offline browser planner with reproducible synthetic tests.
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