Artism: AI-Driven Dual-Engine System for Art Generation and Critique

TL;DR

This paper introduces Artism, a dual-engine AI system combining an artificial artist network and a critique system to simulate art evolution and foster innovative art concepts through interactive, multi-agent collaboration.

Contribution

It presents a novel AI architecture integrating creative and critical components for dynamic art exploration and analysis, advancing computational art methodologies.

Findings

Developed the AIDA social network for AI artists.

Created the Ismism Machine for critical art analysis.

Demonstrated the system's potential in experimental art studies.

Abstract

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.