Regenerative AI Publications
Discover foundational research, white papers, and scientific frameworks defining the next generation of Regenerative AI. Explore closed-loop architectures, cognitive alignment, adaptive decision systems, and governance-ready models designed for the EU AI Act era.
Regen-5 Rahmenwerk: Grundlagen der Regenerativen KI
This working paper introduces the Regen-5 Framework, the first unified scientific architecture for Regenerative Artificial Intelligence. Authored by Aleksandra Pinar (ORCID: 0009-0001-1135-7801), the framework defines a new field of AI research dedicated to decision-making in wicked, complex, and value-conflicted socio-technical systems.
The Regen-5 Framework consists of three core components:
CARES — Cognitive Alignment & Regenerative Systems
RADA — Regenerative Argumentation & Deliberation Architecture
CRDP — Continuous Regenerative Decision Process
Regen-5 Rahmenwerk: Grundlagen der Regenerativen KI
Regen-5 Rahmenwerk: Grundlagen der Regenerativen KI
Regenerative Artificial Intelligence:
A Closed-Loop Architecture for Governance, Alignment, and Adaptive Decision Ecosystems
This white paper defines Regenerative Artificial Intelligence (Regen-AI) as a closed-loop, cognitively aligned, and governance-ready architecture designed for complex, high-risk environments. It introduces a unified framework — including Regen-5, RMC, RADA, CRDP, and CAL — that enables continuous sensing, adaptive reasoning, temporal coherence, and compliance with the EU AI Act. Regenerative AI represents the next generation of responsible, transparent, and resilient decision systems.
