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Modelling human problem solving with data from an online game

Overview of attention for article published in Cognitive Processing, May 2016
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Title
Modelling human problem solving with data from an online game
Published in
Cognitive Processing, May 2016
DOI 10.1007/s10339-016-0767-4
Pubmed ID
Authors

Tim Rach, Alexandra Kirsch

Abstract

Since the beginning of cognitive science, researchers have tried to understand human strategies in order to develop efficient and adequate computational methods. In the domain of problem solving, the travelling salesperson problem has been used for the investigation and modelling of human solutions. We propose to extend this effort with an online game, in which instances of the travelling salesperson problem have to be solved in the context of a game experience. We report on our effort to design and run such a game, present the data contained in the resulting openly available data set and provide an outlook on the use of games in general for cognitive science research. In addition, we present three geometrical models mapping the starting point preferences in the problems presented in the game as the result of an evaluation of the data set.

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The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 27 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Spain 1 4%
Unknown 26 96%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 9 33%
Student > Doctoral Student 5 19%
Student > Master 3 11%
Unspecified 2 7%
Researcher 2 7%
Other 2 7%
Unknown 4 15%
Readers by discipline Count As %
Psychology 7 26%
Computer Science 5 19%
Business, Management and Accounting 2 7%
Unspecified 2 7%
Engineering 2 7%
Other 5 19%
Unknown 4 15%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 15 May 2016.
All research outputs
#20,326,948
of 22,870,727 outputs
Outputs from Cognitive Processing
#293
of 337 outputs
Outputs of similar age
#259,224
of 305,000 outputs
Outputs of similar age from Cognitive Processing
#8
of 8 outputs
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So far Altmetric has tracked 337 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 9.3. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
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