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A survey and critique of multiagent deep reinforcement learning

Overview of attention for article published in Autonomous Agents & Multi-Agent Systems, October 2019
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About this Attention Score

  • One of the highest-scoring outputs from this source (#10 of 105)
  • Good Attention Score compared to outputs of the same age (65th percentile)

Mentioned by

twitter
1 tweeter
wikipedia
1 Wikipedia page

Readers on

mendeley
74 Mendeley
Title
A survey and critique of multiagent deep reinforcement learning
Published in
Autonomous Agents & Multi-Agent Systems, October 2019
DOI 10.1007/s10458-019-09421-1
Authors

Pablo Hernandez-Leal, Bilal Kartal, Matthew E. Taylor

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter 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 74 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 74 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 20 27%
Student > Ph. D. Student 18 24%
Student > Bachelor 12 16%
Researcher 4 5%
Unspecified 4 5%
Other 5 7%
Unknown 11 15%
Readers by discipline Count As %
Computer Science 28 38%
Engineering 21 28%
Mathematics 5 7%
Unspecified 4 5%
Decision Sciences 1 1%
Other 3 4%
Unknown 12 16%

Attention Score in Context

This research output has an Altmetric Attention Score of 4. 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 01 December 2019.
All research outputs
#3,683,032
of 13,999,514 outputs
Outputs from Autonomous Agents & Multi-Agent Systems
#10
of 105 outputs
Outputs of similar age
#94,150
of 272,876 outputs
Outputs of similar age from Autonomous Agents & Multi-Agent Systems
#1
of 1 outputs
Altmetric has tracked 13,999,514 research outputs across all sources so far. This one has received more attention than most of these and is in the 72nd percentile.
So far Altmetric has tracked 105 research outputs from this source. They receive a mean Attention Score of 2.2. This one has done well, scoring higher than 89% 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 272,876 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 65% 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