LATIDIA · Ciberseguridad

Cuando los agentes de IA se encuentran con MEV: arbitraje entre cadenas en la economía agénica

arXiv:2609.17897v1 Tipo de anuncio: nuevo Resumen: Estudiamos el arbitraje entre cadenas cuando los buscadores son agentes de IA autónomos, en lugar de humanos o bots. Modelamos agentes como extractores de arbitraje y Maximal Extractabl

La noticia

arXiv:2609.17897v1 Announce Type: new Abstract: We study cross-chain arbitrage when autonomous AI agents, rather than humans or bots, are the searchers. We model agents as both arbitrage extractors and Maximal Extractable Value targets, derive the optimal trade size for a risk-averse agent under mean-variance utility with stochastic bridge delays, and formalize multi-chain path selection as a belief-weighted online learning problem whose belief estimates converge under a Robbins-Monro schedule. Using 23,000 Uniswap V3 swap events across Ethereum, Arbitrum, and Base, we find that Ethereum-Arbitrum price gaps average 0.044% at 10-second resolution and Arbitrum--Base gaps average 0.013%, so $10,000 trades clear in 63% of L2-L2 windows via CCTP while L1-L2 routes require