Abstract Driven by intelligent technologies, environmental art design is undergoing a paradigm reconstruction from experience dependence to a data-knowledge dual-engine support model. Aiming at the structural defects of the traditional paradigm, such as efficiency bottlenecks, rigid creative boundaries, and sluggish dynamic responses, this study constructs an intelligent design model based on the logic of human-machine symbiosis. Through the integration of three technical modules: the spatial semantic analysis of the generative adversarial network, the multi-objective dynamic optimization of the parametric system, and the immersive collaboration of the augmented reality interface, a closed-loop innovation chain of aesthetic feature vectorization expression - algorithm generation - manual adjustment is formed. Empirical research shows that in typical scenarios such as the activation of cultural heritage and intelligent complexes, this model can increase the efficiency of creative plan generation by 42%, achieve an 82.5% consistency in the evaluation of interdisciplinary experts, enhance the intensity of user emotional resonance by 60% compared with traditional methods, and reduce the construction plan change rate by 55%. This technical framework not only reveals the computable interaction mechanism between algorithm logic and aesthetic laws, but also provides a transformation path with both cognitive breakthroughs and engineering implementation potential for the environmental art field by establishing dynamic weight allocation and ethical review rules. Its methodological system can be extended to the sustainable construction practices of complex systems such as urban renewal and digital cultural heritage protection.
Wang et al. (Mon,) studied this question.