Helping people make better decisions using optimal gamification

Falk Lieder, Thomas L. Griffiths

Research output: Chapter in Book/Report/Conference proceedingConference contribution

11 Scopus citations

Abstract

Game elements like points and levels are a popular tool to nudge and engage students and customers. Yet, no theory can tell us which incentive structures work and how to design them. Here we connect the practice of gamification to the theory of reward shaping in reinforcement learning. We leverage this connection to develop a method for designing effective incentive structures and delineating when gamification will succeed from when it will fail. We evaluate our method in two behavioral experiments. The results of the first experiment demonstrate that incentive structures designed by our method help people make better, less short-sighted decisions and avoid the pitfalls of less principled approaches. The results of the second experiment illustrate that such incentive structures can be effectively implemented using game elements like points and badges. These results suggest that our method provides a principled way to leverage gamification to help people make better decisions.

Original languageEnglish (US)
Title of host publicationProceedings of the 38th Annual Meeting of the Cognitive Science Society, CogSci 2016
EditorsAnna Papafragou, Daniel Grodner, Daniel Mirman, John C. Trueswell
PublisherThe Cognitive Science Society
Pages2075-2080
Number of pages6
ISBN (Electronic)9780991196739
StatePublished - 2016
Externally publishedYes
Event38th Annual Meeting of the Cognitive Science Society: Recognizing and Representing Events, CogSci 2016 - Philadelphia, United States
Duration: Aug 10 2016Aug 13 2016

Publication series

NameProceedings of the 38th Annual Meeting of the Cognitive Science Society, CogSci 2016

Conference

Conference38th Annual Meeting of the Cognitive Science Society: Recognizing and Representing Events, CogSci 2016
Country/TerritoryUnited States
CityPhiladelphia
Period8/10/168/13/16

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Computer Science Applications
  • Human-Computer Interaction
  • Cognitive Neuroscience

Keywords

  • Bounded Rationality
  • Decision-Making
  • Decision-Support
  • Gamification
  • Reinforcement Learning

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