Abstract:
“This paper introduces a user-driven evolutionary algorithm based on Quality Diversity (QD) search. During a design session, the user iteratively selects among presented alternatives and their selections affect the upcoming results. We implement a variation of the MAP-Elites algorithm where the presented alternatives are sampled from a small region (window) of the behavioral space. After a user selection, the window is centered on the selected individual’s behavior characterization, evolution selects parents from within this window to produce offspring, and new alternatives are sampled. Essentially we define an adaptive system of local QD search, where the user’s selections guide the search towards specific regions of the behavioral space. The system is tested on the generation of architectural layouts, a constrained optimization task, leveraging QD search through a two-archive approach.”
Citation:
Konstantinos Sfikas, Antonios Liapis and Georgios N. Yannakakis: “Controllable Exploration of a Design Space via Interactive Quality Diversity,” in Proceedings of the Genetic and Evolutionary Computation Conference Companion, 2023
Bibtex:
@inproceedings{sfikas2023controllable,
author={Konstantinos Sfikas and Antonios Liapis and Georgios N. Yannakakis},
title={Controllable Exploration of a Design Space via Interactive Quality Diversity},
booktitle={Proceedings of the Genetic and Evolutionary Computation Conference Companion},
year={2023},
}