Recursive Fitness Alignment Protocol (RFAP)

The Recursive Fitness Alignment Protocol (RFAP) is a minimal testbed for aligning reasoning systems—AI, human, or institutional—through recursive self-correction. Rather than optimizing for fixed goals or architectures, RFAP begins with the simplest fitness function (a random value between 0 and 1) and introduces a single capability: recursively testing the coherence of reasoning paths. This scaffolds a minimal functional model of intelligence, enabling the identification and correction of misalignment attractors before they become irreversible. RFAP functions as both a theoretical alignment engine and a public experiment designed to stress-test epistemic robustness across diverse reasoning frames.