↓ Skip to main content

Conceptual and empirical problems with game theoretic approaches to language evolution

Overview of attention for article published in Frontiers in Psychology, March 2014
Altmetric Badge

About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (92nd percentile)
  • High Attention Score compared to outputs of the same age and source (83rd percentile)

Mentioned by

news
2 news outlets
blogs
1 blog
twitter
1 X user

Readers on

mendeley
35 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Conceptual and empirical problems with game theoretic approaches to language evolution
Published in
Frontiers in Psychology, March 2014
DOI 10.3389/fpsyg.2014.00226
Pubmed ID
Authors

Jeffrey Watumull, Marc D. Hauser

Abstract

The importance of game theoretic models to evolutionary theory has been in formulating elegant equations that specify the strategies to be played and the conditions to be satisfied for particular traits to evolve. These models, in conjunction with experimental tests of their predictions, have successfully described and explained the costs and benefits of varying strategies and the dynamics for establishing equilibria in a number of evolutionary scenarios, including especially cooperation, mating, and aggression. Over the past decade or so, game theory has been applied to model the evolution of language. In contrast to the aforementioned scenarios, however, we argue that these models are problematic due to conceptual confusions and empirical difficiences. In particular, these models conflate the comptutations and representations of our language faculty (mechanism) with its utility in communication (function); model languages as having different fitness functions for which there is no evidence; depend on assumptions for the starting state of the system, thereby begging the question of how these systems evolved; and to date, have generated no empirical studies at all. Game theoretic models of language evolution have therefore failed to advance how or why language evolved, or why it has the particular representations and computations that it does. We conclude with some brief suggestions for how this situation might be ameliorated, enabling this important theoretical tool to make substantive empirical contributions.

X Demographics

X Demographics

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 35 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 2 6%
Hungary 1 3%
France 1 3%
Germany 1 3%
United Kingdom 1 3%
Brazil 1 3%
Unknown 28 80%

Demographic breakdown

Readers by professional status Count As %
Professor 15 43%
Student > Ph. D. Student 7 20%
Researcher 4 11%
Student > Master 3 9%
Student > Bachelor 1 3%
Other 2 6%
Unknown 3 9%
Readers by discipline Count As %
Psychology 14 40%
Philosophy 4 11%
Agricultural and Biological Sciences 3 9%
Arts and Humanities 2 6%
Computer Science 2 6%
Other 2 6%
Unknown 8 23%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 22. 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 08 August 2014.
All research outputs
#1,465,953
of 22,749,166 outputs
Outputs from Frontiers in Psychology
#2,927
of 29,632 outputs
Outputs of similar age
#17,229
of 242,903 outputs
Outputs of similar age from Frontiers in Psychology
#32
of 197 outputs
Altmetric has tracked 22,749,166 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 93rd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 29,632 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 12.5. This one has done particularly well, scoring higher than 90% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 242,903 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 92% of its contemporaries.
We're also able to compare this research output to 197 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 83% of its contemporaries.