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Related Experiment Video

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Multimedia Battery for Assessment of Cognitive and Basic Skills in Mathematics BM-PROMA
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Inferring Mathematical Equations Using Crowdsourcing.

Szymon Wasik1,2, Filip Fratczak1, Jakub Krzyskow1

  • 1Institute of Computing Science, Poznan University of Technology, Poznan, Poland.

Plos One
|December 30, 2015
PubMed
Summary
This summary is machine-generated.

Crowdsourced serious games can discover mathematical equations explaining dynamic systems. This approach, using collective intelligence, rivals artificial intelligence in accuracy for certain equation complexities.

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Area of Science:

  • Computational Science
  • Data Science
  • Mathematical Modeling

Background:

  • Crowdsourcing leverages large networks for problem-solving.
  • Crowdsourced serious games combine gaming with scientific objectives.
  • Discovering mathematical equations for dynamic systems is crucial.

Purpose of the Study:

  • To evaluate crowdsourcing via serious games for discovering mathematical equations.
  • To compare crowdsourced equation discovery with artificial intelligence (AI) symbolic regression.
  • To assess the potential of collective intelligence in scientific problem-solving.

Main Methods:

  • Developed an internet game where players design 'spaceships' representing equations.
  • Enabled player collaboration to refine solutions.
  • Tested the game with hundreds of players and analyzed results.

Main Results:

  • Crowdsourced equations achieved high precision, comparable to analytical solutions.
  • The game-derived equations outperformed AI symbolic regression (Eureqa) for certain complexities.
  • Collaborative efforts significantly improved solution quality.

Conclusions:

  • Crowdsourced serious games show significant potential for scientific discovery.
  • This approach effectively harnesses collective intelligence for complex problem-solving.
  • The game provides an accessible platform for non-experts to contribute to mathematical modeling.