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Terrain-adaptive locomotion skills using deep reinforcement learning

Overview of attention for article published in ACM Transactions on Graphics, July 2016
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (60th percentile)

Mentioned by

patent
2 patents

Citations

dimensions_citation
85 Dimensions

Readers on

mendeley
349 Mendeley
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Title
Terrain-adaptive locomotion skills using deep reinforcement learning
Published in
ACM Transactions on Graphics, July 2016
DOI 10.1145/2897824.2925881
Authors

Xue Bin Peng, Glen Berseth, Michiel van de Panne

Mendeley readers

The data shown below were compiled from readership statistics for 349 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 4 1%
Germany 3 <1%
Austria 1 <1%
Ireland 1 <1%
Chile 1 <1%
United Kingdom 1 <1%
Belgium 1 <1%
Japan 1 <1%
Portugal 1 <1%
Other 0 0%
Unknown 335 96%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 91 26%
Student > Master 81 23%
Researcher 45 13%
Student > Bachelor 40 11%
Student > Doctoral Student 14 4%
Other 36 10%
Unknown 42 12%
Readers by discipline Count As %
Computer Science 183 52%
Engineering 100 29%
Neuroscience 6 2%
Agricultural and Biological Sciences 6 2%
Physics and Astronomy 3 <1%
Other 8 2%
Unknown 43 12%

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 12 January 2021.
All research outputs
#5,461,055
of 16,983,585 outputs
Outputs from ACM Transactions on Graphics
#807
of 2,138 outputs
Outputs of similar age
#74,640
of 191,085 outputs
Outputs of similar age from ACM Transactions on Graphics
#1
of 1 outputs
Altmetric has tracked 16,983,585 research outputs across all sources so far. This one is in the 47th percentile – i.e., 47% of other outputs scored the same or lower than it.
So far Altmetric has tracked 2,138 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.3. This one is in the 10th percentile – i.e., 10% of its peers scored the same or lower than it.
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 191,085 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 60% of its contemporaries.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them