Abstract
Human designers often work in a visual design space, projecting step-by-step design progression through evolving mental images. The strategic evolution of that design leverages heuristics based on experience and domain knowledge. The methodology presented in this paper brings together the visual nature of design problem solving and design heuristics in a deep learning computational agent framework that emulates and enables human-mirrored design. When applied to a truss design task, results demonstrate superior results to those of human designers who provided the initial data.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 355-364 |
| Number of pages | 10 |
| Journal | Proceedings of the Design Society: DESIGN Conference |
| Volume | 1 |
| DOIs | |
| State | Published - 2020 |
| Event | 16th International Design Conference, DESIGN 2020 - Virtual, Online Duration: Oct 26 2020 → Oct 29 2020 |
All Science Journal Classification (ASJC) codes
- Engineering (miscellaneous)
- Industrial and Manufacturing Engineering
- Modeling and Simulation
- Computer Science Applications
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