EquiVerse AI – Sistema de Inteligência Artificial não Antropocêntrica para a Modelagem da Interação Humano-Animal em Corridas de Cavalo
Abstract
This article presents a non-anthropocentric artificial intelligence architecture designed to model complex human–animal interactions in competitive environments.
By integrating computer vision, statistical learning, and game theory, the proposed system moves beyond human-centered assumptions of cognition, treating animal behavior as an autonomous decision-making process rather than a derivative of human intent.
The work explores how probabilistic modeling, sensor data, and strategic interaction can be combined to produce deterministic and quantitative estimations in environments characterized by uncertainty, non-linearity, and asymmetric incentives. Beyond its immediate application, the framework contributes to broader discussions on non-anthropocentric intelligence, behavioral modeling, and decision systems in complex adaptive domains.
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