Optimally Designing Games for Cognitive Science Research

Anna N. Rafferty, Matei Zaharia, Thomas L. Griffiths

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

6 Scopus citations

Abstract

Collecting cognitive science data using games has the potential to be a powerful tool for recruiting participants and increasing their motivation. However, designing games that provide useful data is a difficult task that often requires significant trial and error. In this work, we consider how to apply ideas from optimal experiment design to designing games for cognitive science experiments. We use Markov decision processes to model players’ actions within a game, and then make inferences about the parameters of a cognitive model from these actions. We present a general framework for finding games with high expected information gain based on this approach. We apply this framework to Boolean concept learning, inferring the difficulty of Boolean concepts from participants’ behavior. We show that using games with higher expected information gain allows us to make this inference more efficiently.

Original languageEnglish (US)
Title of host publicationBuilding Bridges Across Cognitive Sciences Around the World - Proceedings of the 34th Annual Meeting of the Cognitive Science Society, CogSci 2012
EditorsNaomi Miyake, David Peebles, Richard P. Cooper
PublisherThe Cognitive Science Society
Pages893-898
Number of pages6
ISBN (Electronic)9780976831884
StatePublished - 2012
Externally publishedYes
Event34th Annual Meeting of the Cognitive Science Society: Building Bridges Across Cognitive Sciences Around the World, CogSci 2012 - Sapporo, Japan
Duration: Aug 1 2012Aug 4 2012

Publication series

NameBuilding Bridges Across Cognitive Sciences Around the World - Proceedings of the 34th Annual Meeting of the Cognitive Science Society, CogSci 2012

Conference

Conference34th Annual Meeting of the Cognitive Science Society: Building Bridges Across Cognitive Sciences Around the World, CogSci 2012
Country/TerritoryJapan
CitySapporo
Period8/1/128/4/12

All Science Journal Classification (ASJC) codes

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

Keywords

  • Markov decision process
  • computer games
  • concept learning
  • optimal experiment design

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