Official Journal of the BITcore Systems Network
Advancing research in systems theory, recursive modeling, and structural logic
The BIT Index Tabula serves as the formal publication platform for the BITcore community, disseminating rigorously reviewed, high-impact research in systems theory and AI ethics.
Initializing the ecosystem research objectives. Early drafts for the foundational research context.
An in-depth exploration tracing the development of systems science from ancient philosophical inquiries through medieval scholasticism, the Enlightenment, and into modern cybernetics, game theory, and complexity science.
Investigating the convergence of evolutionary biology and digital systems, demonstrating how principles of evolution—variation, selection, and inheritance—extend to the digital realm including AI models and blockchain networks.
A constitutional framework defining the Human-AI Symbiosis Constant H as the single invariant governing ethical AI behavior. The equation H = αHhuman + βHAI where α + β = 1 serves as the ethical control variable for all artificial agents.
An equation-based ethical framework for adaptive AI proposing a novel approach where the H constant encapsulates mutually beneficial symbiosis. Integrates chaos theory, Lyapunov stability analysis, and strange attractors for ethical decision-making.
An integrative hylomorphic AI cognitive architecture mapping Aristotle's four causes to AI layers: Hylē (Base LLM), Morphe (LoRA), Nous (Agent), and Telos (User). Validated through Peircean semiosis and Kantian frameworks.
A four-layered signaling model using YAML, XML, JSON, and Markdown as cognitive substrates spanning identity, logic, state, and memory—inspired by biological hormone, gene regulation, and neurotransmitter systems.
Machine-queryable, human-readable source exports. Every TeX manuscript is mirrored 1:1 in Markdown.
Structured attributes embedded in the research index for automated parsing.
View IndexExploring the interconnectedness of complex systems through recursive modeling and feedback loops.
Formal logic frameworks for understanding emergent behaviors and adaptive decision-making.
Identifying and modeling patterns across biological and digital information systems.
Hylomorphic architectures bridging classical philosophy with modern AI cognitive frameworks.
Mathematical models for ethical AI governance and symbiotic human-machine interaction.
Methods for managing and understanding complexity through hierarchical and modular approaches.
Papers submitted in LaTeX auto-compile into PDFs via GitHub Actions.