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Bibliographic Details
Main Authors: Liu, Shuai, Tian, Yiqing, Chen, Yang, Sola, Mar Canet
Format: Preprint
Published: 2025
Subjects:
Online Access:https://arxiv.org/abs/2512.15710
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Table of Contents:
  • This paper proposes a dual-engine AI architectural method designed to address the complex problem of exploring potential trajectories in the evolution of art. We present two interconnected components: AIDA (an artificial artist social network) and the Ismism Machine, a system for critical analysis. The core innovation lies in leveraging deep learning and multi-agent collaboration to enable multidimensional simulations of art historical developments and conceptual innovation patterns. The framework explores a shift from traditional unidirectional critique toward an intelligent, interactive mode of reflexive practice. We are currently applying this method in experimental studies on contemporary art concepts. This study introduces a general methodology based on AI-driven critical loops, offering new possibilities for computational analysis of art.