Inverse Mapping with Sensitivity Analysis for Partial Selection in Interactive Evolution
Inhaltsverzeichnis
Referenz
Jonathan Eisenmann, Matthew Lewis, Rick Parent: Inverse Mapping with Sensitivity Analysis for Partial Selection in Interactive Evolution. In: EvoMUSART 2013, S. 72-84.
DOI
http://link.springer.com/10.1007/978-3-642-36955-1_7
Abstract
Evolutionary algorithms have shown themselves to be useful interactive design tools. However, current algorithms only receive feedback about candidate fitness at the whole-candidate level. In this paper we describe a model-free method, using sensitivity analysis, which allows designers to provide fitness feedback to the system at the component level. Any part of a candidate can be marked by the designer as interesting (i.e. having high fitness). This has the potential to improve the design experience in two ways: (1) The finer-grain guidance provided by partial selections facilitates more precise iteration on design ideas so the designer can maximize her energy and attention. (2) When steering the evolutionary system with more detailed feedback, the designer may discover greater feelings of satisfaction with and ownership over the final designs.
Extended Abstract
Bibtex
Links
Full Text
[extern file]
