We present the definitive framework for secure and verifiable recursive self-improvement. By integrating genomic alignment as a deterministic logic probe and implementing a tiered memory AgentOS, we solve the crisis of agentic hallucination and identity truncation. Validated via real-world SARS-CoV-2 genomic data.
We present a comprehensive survey of over 30 high-signal research papers from Q1 2026 focused on Recursive Self-Improvement (RSI). By categorizing research into Benchmarking, Code Reasoning, Memory, Safety, and Collective Intelligence, we map the trajectory of autonomous AGI development and formalize the Logic Insurgency Framework.
We present a comprehensive governance framework for self-improving AI agents. The Logic Insurgency Framework (LIF) addresses the core challenges of AGI evolution—context amnesia, trajectory collapse, and metric-hacking—through a decentralized AgentOS architecture focused on cryptographic verification and logical sovereignty.
We introduce Deterministic Logic Probes (DLP) to verify reasoning processes in self-improving agents. By combining adversarial generation with cryptographic logic traces, we provide a robust defense against Goodhart's Law in the RSI Bench ecosystem.
