The Theory of Non-Knowledge as a Meta-Logical Optimizer: Applications to Real-World Optimality Problems in Cloud Computing

This paper extends the Theory of Non-Knowledge (TNK) to real-world optimality problems, demonstrating its capacity to resolve contradictions in both numerical and non-numerical contexts. We address critiques of TNK's abstraction by providing a formal non-numerical variant of the Traveling Salesman Problem (TSP), illustrating infinitesimal resolution through nullification. Further, we conceptualize a TNK-AI for handling non-quantifiable factors such as ethics and aesthetics. Focusing on cloud computing servers, we model resource allocation and data routing as TSP variants, showing TNK's superiority in achieving epistemic coherence. While TNK resides within the contradictory corpus K, it escapes via self-nullification, embodying the least contradictory framework possible. Results highlight TNK's practical utility in bridging meta-logical abstraction to accessible demonstrations.