Abstract
Human computation, applying human problem solving to computational problems, has shown promise in numerous applications. In some applications of human computation, it may be useful to find not just a single best solution, but a variety of good solutions with different properties that can be used for further analysis. Recent work in quality-diversity search, such as MAP-Elites, has developed techniques that aim to find a variety of solutions. Thus, in this work, we explore the potential of combining quality-diversity and human computation approaches. We ran a crowdsourced study of the Traveling Salesperson Problem in which some participants were provided with a visualization of their MAP-Elites archive and some were not. We did not find a difference in the quality of the best solutions found by participants between the two groups. However, we did find that participants provided with the archive visualization searched more of the MAP-Elites behavior space than those without the visualization. This demonstrates potential for quality-diversity approaches to lead to finding a wider variety of solutions in human computation search.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.