Formal Proofs
8 proofs · 27 theorems
Machine-checked proofs for AI agent systems, ML frameworks, and distributed compute infrastructure.
Formal proof that Group Relative Policy Optimization converges to a stable policy under bounded reward variance. Establishes monotonic improvement guarantees and KL-divergence bounds for multi-agent training.
Proof of Byzantine fault tolerance for federated agent coordination. Establishes safety under f < n/3 malicious agents and liveness under partial synchrony for distributed decision-making.
Formal verification of the Jin multimodal architecture proving type safety across vision-language-audio pipelines. Establishes that cross-modal attention preserves embedding dimensionality and semantic alignment.
Proof that Model Context Protocol maintains causal message ordering under concurrent tool invocations. Establishes exactly-once delivery semantics and context window consistency for agent-model communication.
Formal verification of tensor operation correctness in the Candle ML framework. Proves shape preservation across broadcast operations, gradient flow through computational graphs, and numerical stability of softmax.
Proof of correctness for the LLM gateway routing layer. Establishes that weighted load balancing preserves fairness, rate limiting prevents starvation, and fallback routing guarantees availability under partial provider failure.
Establishes convergence bounds for agents that recursively improve their own policy. Proves that improvement magnitude is monotonically decreasing and bounded, preventing divergence under the capability amplification loop.
Formal proof of test harness completeness for the Hanzo agent evaluation framework. Establishes that the harness covers all reachable agent states and that no observable behavior escapes the test oracle.