Modern operational defense systems increasingly rely on automated agents, distributed sensing networks, real-time coordination substrates, and heterogeneous decision pipelines. These systems operate under strict requirements for safety, determinism, auditability, and rapid response. However, existing automation frameworks exhibit nondeterministic behavior due to probabilistic models, asynchronous event ordering, inconsistent sensor fusion, and multi-agent disagreement. This nondeterminism undermines reproducibility, safety envelopes, and operational trust. I introduce Lume-Def, a deterministic governance substrate for defense-grade operational environments. Built on the DAIGS foundation, Lume-Def integrates the invariant-preserving safety layer of Lume-V with the multi-agent arbitration and collective cognition capabilities of Lume-X. Lume-Def defines operational invariants, threat-surface envelopes, deterministic override mechanisms, multi-agent convergence rules, and certificate-based operational truth records tailored to real-time defense workflows. We formalize the Lume-Def architecture, define its operational semantics, and present constructive proofs demonstrating invariant preservation, deterministic override correctness, multi-agent convergence under adversarial conditions, and replay-identical execution. I evaluate Lume-Def in a simulated defense environment with fault injection, sensor degradation, adversarial noise, timing instability, and multi-agent conflict. Results show that Lume-Def enforces deterministic safety envelopes, maintains certificate-chain integrity, and ensures reproducible outcomes even under degraded or adversarial conditions.
Ronald Jason Andrews (Thu,) studied this question.