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MODELING A STRATEGIC HUMAN ENGINEERING DESIGN PROCESS: HUMAN-INSPIRED HEURISTIC GUIDANCE THROUGH LEARNED VISUAL DESIGN AGENTS

Part of: Design Support Tools

Published online by Cambridge University Press:  11 June 2020

L. Puentes ,
A. Raina ,
J. Cagan  and
C. McComb
L. Puentes
Affiliation:
The Pennsylvania State University, United States of America
A. Raina
Affiliation:
Carnegie Mellon University, United States of America
J. Cagan*
Affiliation:
Carnegie Mellon University, United States of America
C. McComb
Affiliation:
The Pennsylvania State University, United States of America
*
*cagan@cmu.edu

Abstract

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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.

Keywords

artificial intelligence (AI)engineering designdesign automationdeep learningheuristics
Type
Article
Information
Proceedings of the Design Society: DESIGN Conference , Volume 1 , May 2020 , pp. 355 - 364
Creative Commons
Creative Common License - CCCreative Common License - BYCreative Common License - NCCreative Common License - ND
This is an Open Access article, distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives licence (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is unaltered and is properly cited. The written permission of Cambridge University Press must be obtained for commercial re-use or in order to create a derivative work.
Copyright
The Author(s), 2020. Published by Cambridge University Press

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