Research Papers
// Advancing the frontiers of artificial general intelligence through rigorous research and breakthrough discoveries
MonArch: A Neuro-Symbolic Framework for Knowledge Coherence in Distributed AGI Systems via Time-Sensitive KL Divergence
Chief Scientist, ConversionZilla.com, Newport Beach, CA
This paper addresses a fundamental AGI challenge: maintaining knowledge coherence in complex, adaptive multi-agent systems. We introduce MonArch, a neuro-symbolic framework unifying distributed architectural knowledge across cognitive components. MonArch combines time-sensitive Kullback-Leibler divergence minimization with Horn clause reasoning, enabling both belief optimization and logical constraint enforcement. This hybrid approach allows AGI systems to monitor their own knowledge, detect inconsistencies, and adapt while maintaining coherence.
Research Impact
// Advancing the state of AGI research