Title
Algorithm Discovery By Protein Folding Game Players
Abstract
Foldit is a multiplayer online game in which players collaborate and compete to create accurate protein structure models. For specific hard problems, Foldit player solutions can in some cases outperform state-of-the-art computational methods. However, very little is known about how collaborative gameplay produces these results and whether Foldit player strategies can be formalized and structured so that they can be used by computers. To determine whether high performing player strategies could be collectively codified, we augmented the Foldit gameplay mechanics with tools for players to encode their folding strategies as "recipes" and to share their recipes with other players, who are able to further modify and redistribute them. Here we describe the rapid social evolution of player-developed folding algorithms that took place in the year following the introduction of these tools. Players developed over 5,400 different recipes, both by creating new algorithms and by modifying and recombining successful recipes developed by other players. The most successful recipes rapidly spread through the Foldit player population, and two of the recipes became particularly dominant. Examination of the algorithms encoded in these two recipes revealed a striking similarity to an unpublished algorithm developed by scientists over the same period. Benchmark calculations show that the new algorithm independently discovered by scientists and by Foldit players outperforms previously published methods. Thus, online scientific game frameworks have the potential not only to solve hard scientific problems, but also to discover and formalize effective new strategies and algorithms.
Year
DOI
Venue
2011
10.1073/pnas.1115898108
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
Keywords
Field
DocType
citizen science, crowd-sourcing, optimization, structure prediction, strategy
Population,ENCODE,Social evolution,Computer science,Algorithm,Citizen science,The Internet
Journal
Volume
Issue
ISSN
108
47
0027-8424
Citations 
PageRank 
References 
77
3.71
2
Authors
8
Name
Order
Citations
PageRank
Firas Khatib142832.00
Seth Cooper274558.65
Michael D. Tyka3814.64
Kefan Xu4773.71
Ilya Makedon5896.24
Zoran Popović64353279.05
Baker, D.719615.26
Foldit Players837926.81