空格(标点符号)
计算机科学
组合博弈论
简单(哲学)
人工智能
理论计算机科学
人机交互
数据科学
机器学习
博弈论
序贯博弈
数学
认识论
操作系统
哲学
数理经济学
作者
Seth Cooper,Firas Khatib,Adrien Treuille,Janos Barbero,Jeehyung Lee,Michael Beenen,Andrew Leaver‐Fay,David Baker,Zoran Popović,Foldit Players
出处
期刊:Nature
[Springer Nature]
日期:2010-08-01
卷期号:466 (7307): 756-760
被引量:1140
摘要
People exert large amounts of problem-solving effort playing computer games. Simple image- and text-recognition tasks have been successfully 'crowd-sourced' through games, but it is not clear if more complex scientific problems can be solved with human-directed computing. Protein structure prediction is one such problem: locating the biologically relevant native conformation of a protein is a formidable computational challenge given the very large size of the search space. Here we describe Foldit, a multiplayer online game that engages non-scientists in solving hard prediction problems. Foldit players interact with protein structures using direct manipulation tools and user-friendly versions of algorithms from the Rosetta structure prediction methodology, while they compete and collaborate to optimize the computed energy. We show that top-ranked Foldit players excel at solving challenging structure refinement problems in which substantial backbone rearrangements are necessary to achieve the burial of hydrophobic residues. Players working collaboratively develop a rich assortment of new strategies and algorithms; unlike computational approaches, they explore not only the conformational space but also the space of possible search strategies. The integration of human visual problem-solving and strategy development capabilities with traditional computational algorithms through interactive multiplayer games is a powerful new approach to solving computationally-limited scientific problems.
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