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X Demographics
Mendeley readers
Attention Score in Context
| Chapter title |
Deep Reinforcement Learning: An Overview
|
|---|---|
| Chapter number | 32 |
| Book title |
Proceedings of SAI Intelligent Systems Conference (IntelliSys) 2016
|
| Published in |
arXiv, September 2016
|
| DOI | 10.1007/978-3-319-56991-8_32 |
| Book ISBNs |
978-3-31-956990-1, 978-3-31-956991-8
|
| Authors |
Seyed Sajad Mousavi, Michael Schukat, Enda Howley, Mousavi, Seyed Sajad, Schukat, Michael, Howley, Enda |
X Demographics
The data shown below were collected from the profiles of 35 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Japan | 3 | 9% |
| United States | 2 | 6% |
| Germany | 2 | 6% |
| United Kingdom | 2 | 6% |
| Australia | 2 | 6% |
| Sao Tome and Principe | 1 | 3% |
| Turkey | 1 | 3% |
| China | 1 | 3% |
| North Macedonia | 1 | 3% |
| Other | 3 | 9% |
| Unknown | 17 | 49% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 26 | 74% |
| Scientists | 7 | 20% |
| Science communicators (journalists, bloggers, editors) | 2 | 6% |
Mendeley readers
The data shown below were compiled from readership statistics for 4,396 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 11 | <1% |
| Germany | 7 | <1% |
| Canada | 4 | <1% |
| France | 3 | <1% |
| Korea, Republic of | 2 | <1% |
| Japan | 2 | <1% |
| China | 2 | <1% |
| India | 1 | <1% |
| United Kingdom | 1 | <1% |
| Other | 5 | <1% |
| Unknown | 4358 | 99% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 891 | 20% |
| Student > Master | 821 | 19% |
| Researcher | 495 | 11% |
| Student > Bachelor | 429 | 10% |
| Other | 214 | 5% |
| Other | 472 | 11% |
| Unknown | 1074 | 24% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 1855 | 42% |
| Engineering | 749 | 17% |
| Mathematics | 87 | 2% |
| Physics and Astronomy | 86 | 2% |
| Economics, Econometrics and Finance | 49 | 1% |
| Other | 390 | 9% |
| Unknown | 1180 | 27% |
Attention Score in Context
This research output has an Altmetric Attention Score of 23. 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 30 November 2023.
All research outputs
#1,613,624
of 25,166,481 outputs
Outputs from arXiv
#25,422
of 1,028,328 outputs
Outputs of similar age
#27,985
of 328,209 outputs
Outputs of similar age from arXiv
#354
of 13,625 outputs
Altmetric has tracked 25,166,481 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 1,028,328 research outputs from this source. They receive a mean Attention Score of 4.1. This one has done particularly well, scoring higher than 97% 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 328,209 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 91% of its contemporaries.
We're also able to compare this research output to 13,625 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 97% of its contemporaries.