Aplysia: A Neuroevolutionary Generative Design Tool

摘要: This work presents the development of a proof-of-concept generative design tool for the AEC industry, named Aplysia. Aplysia has the capability to provide the designer with the ability to produce emergent design solutions from multi-objective criteria without the tradeoff between number of objectives and computational resources. easily and rapidly produce varied, performanceoriented geometries suited for concept design. The current inefficiencies with existing generative design tools are primarily due to the underlying algorithms, such as evolutionary algorithms which require significant computational resources due to large search spaces, and inconsistencies between industry requirements and provided features, such as requiring domain expert input to use these tools which make it inaccessible to many users. We present the novel use of a compositional pattern-producing network (CPPN) and the Neuro-Evolution of Augmenting Topologies (NEAT) algorithm for a building-scale structure. This paper details the software development methodology to build the tool, driven by a user-centric approach. Requirements gathering, which framed the scope of Aplysia, was completed through a use case study. The user and technical requirements were translated into a modular system architecture and user-friendly GUI. Aplysia was experimentally tested for the design of a lightweight, free-standing canopy. Our initial findings show that Aplysia improves the generative design workflow for the test case, which we argue is more adaptable to real-world AEC design problems and outline further improvements in the continual development of Aplysia.