By H. Overman (opsec.ee@pm.me) © 2025 \
RTKA recursive (infinite recursion) ternary, unknown preservation, confidence propagation and early termination
RTKA represents a mathematically rigorous formal logic framework designed for computational uncertainty reasoning in systems requiring deterministic guarantees. Unlike statistical or machine learning approaches to confidence scoring, this framework implements recursive ternary logic operations with formal proofs and algebraic guarantees for uncertainty propagation. The confidence quantification follows established mathematical principles rather than probabilistic estimates, making it suitable for safety-critical applications in sensor fusion, fault-tolerant systems, and formal verification domains where mathematical correctness remains paramount.
The framework extends strong three-valued logic through recursive processing of ternary truth values represented as T = {-1, 0, 1}, corresponding to FALSE, UNKNOWN, and TRUE states respectively. This mathematical foundation incorporates sophisticated confidence propagation mechanisms that preserve uncertainty throughout the computational pipeline, resolving ambiguity only when logical determination becomes mathematically necessary. The implementation achieves exceptional computational efficiency with O(n) time complexity and O(1) space requirements, suitable for real-time applications in resource-constrained environments.
The architecture enables critical services across industries demanding robust handling of uncertainty and incomplete data. This capability proves essential for artificial intelligence systems operating with partial information, sensor fusion networks processing conflicting inputs, and enterprise decision-making platforms where complete information rarely exists. The system provides deterministic processing methods for inherently non-deterministic problems while maintaining mathematical rigor and operational efficiency throughout the decision pipeline.
RTKA is fundamentally different from any known ternary algorithm, which treats their three states as final outcomes rather than gateways to deeper uncertainty resolution.
The framework represents a unique contribution to computational logic, distinct from existing approaches to uncertainty reasoning.
Historical Context - Development history and theoretical foundations
Technical Distinction - Comparison with related systems
Sensor Implementation - Sensor demonstartion implementation
Python Implementation - Reference implementation and validation suite
Collaboration and technical feedback are welcome. For questions about core development, module integration patterns, or research collaboration opportunities, please contact the author. Note that response times may vary as this is an active research project without dedicated support resources.
This project is licensed under Dual Licensing. See the LICENSE file for details.
For commercial licensing inquiries, please contact opsec.ee@pm.me
This software implements the mathematically sound Recursive Ternary Knowledge Algorithm (RTKA) based on validated Kleene logic principles. While the algorithm itself is theoretically correct and suitable for commercial applications under appropriate licensing, this particular implementation is experimental research code that may not be suitable for production use. The codebase demonstrates algorithmic feasibility but lacks the comprehensive testing, optimization, and hardening required for deployment. Users assume all risks associated with using this proof-of-concept implementation. For commercial licensing or production-grade development inquiries, contact opsec.ee@pm.me