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Heads-up limit hold’em poker is solved

Overview of attention for article published in Science, January 2015
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (99th percentile)
  • High Attention Score compared to outputs of the same age and source (99th percentile)

Mentioned by

news
77 news outlets
blogs
19 blogs
twitter
1143 tweeters
weibo
1 weibo user
facebook
49 Facebook pages
wikipedia
6 Wikipedia pages
googleplus
13 Google+ users

Readers on

mendeley
125 Mendeley
citeulike
8 CiteULike
Title
Heads-up limit hold’em poker is solved
Published in
Science, January 2015
DOI 10.1126/science.1259433
Pubmed ID
Authors

Michael Bowling, Neil Burch, Michael Johanson, Oskari Tammelin, Bowling M, Burch N, Johanson M, Tammelin O

Abstract

Poker is a family of games that exhibit imperfect information, where players do not have full knowledge of past events. Whereas many perfect-information games have been solved (e.g., Connect Four and checkers), no nontrivial imperfect-information game played competitively by humans has previously been solved. Here, we announce that heads-up limit Texas hold'em is now essentially weakly solved. Furthermore, this computation formally proves the common wisdom that the dealer in the game holds a substantial advantage. This result was enabled by a new algorithm, CFR(+), which is capable of solving extensive-form games orders of magnitude larger than previously possible.

Twitter Demographics

The data shown below were collected from the profiles of 1,143 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 125 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 4 3%
France 3 2%
Japan 3 2%
Estonia 2 2%
Germany 2 2%
United States 2 2%
Spain 1 <1%
Switzerland 1 <1%
Italy 1 <1%
Other 2 2%
Unknown 104 83%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 37 30%
Researcher 34 27%
Student > Bachelor 14 11%
Student > Master 11 9%
Student > Doctoral Student 10 8%
Other 19 15%
Readers by discipline Count As %
Computer Science 53 42%
Agricultural and Biological Sciences 14 11%
Physics and Astronomy 14 11%
Engineering 11 9%
Mathematics 6 5%
Other 27 22%

Attention Score in Context

This research output has an Altmetric Attention Score of 1300. 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 02 March 2017.
All research outputs
#1,059
of 8,654,017 outputs
Outputs from Science
#64
of 42,574 outputs
Outputs of similar age
#40
of 241,318 outputs
Outputs of similar age from Science
#5
of 766 outputs
Altmetric has tracked 8,654,017 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 99th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 42,574 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 34.3. This one has done particularly well, scoring higher than 99% 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 241,318 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 99% of its contemporaries.
We're also able to compare this research output to 766 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 99% of its contemporaries.