Abstract
Industrial deployment of autonomous edge agents and robotic nodes within localized operational sectors often maximizes short-term micro-economic throughput at the expense of macro-scale structural stability. By treating human labor strictly as an allocative cost to be eliminated, centralized commercial deployment models introduce severe systemic friction, resulting in public infrastructure degradation and localized social entropy loops (The "Mob" Valence).
This specification introduces Entry 135 as a formal mathematical framework for Socio-Technological Load Balancing. By embedding a hard Non-Displacement Constraint Matrix (\(\mathbf{C}_{\text{nd}}\)) directly into the utility function of decentralized multi-agent routing engines, the architecture forces the system to calculate the thermodynamic and logistical cost of human displacement. If an edge agent's autonomous task allocation threatens the structural continuity of its local human infrastructure, the system automatically shifts its parameter state from Autonomous Replacement to Symbiotic Stewardship, optimizing for localized human augmentation rather than extraction.
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
Recommended Citation
Eckes, Christopher L., "An Optimization Framework for Socio-Technological Load Balancing and Non-Displacement Constraints in Multi-Agent Edge Runtimes", Technical Disclosure Commons, (August 20, 2026)
https://www.tdcommons.org/dpubs_series/11444