| Title |
Preference-based reinforcement learning: a formal framework and a policy iteration algorithm
|
|---|---|
| Published in |
Machine Learning, August 2012
|
| DOI | 10.1007/s10994-012-5313-8 |
| Authors |
Johannes Fürnkranz, Eyke Hüllermeier, Weiwei Cheng, Sang-Hyeun Park |
X Demographics
The data shown below were collected from the profiles of 3 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 | 1 | 33% |
| Unknown | 2 | 67% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 3 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 131 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Germany | 1 | <1% |
| Switzerland | 1 | <1% |
| Netherlands | 1 | <1% |
| France | 1 | <1% |
| Slovenia | 1 | <1% |
| Japan | 1 | <1% |
| Unknown | 125 | 95% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 35 | 27% |
| Student > Master | 21 | 16% |
| Researcher | 20 | 15% |
| Professor > Associate Professor | 7 | 5% |
| Student > Bachelor | 6 | 5% |
| Other | 14 | 11% |
| Unknown | 28 | 21% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 66 | 50% |
| Engineering | 17 | 13% |
| Psychology | 4 | 3% |
| Mathematics | 3 | 2% |
| Social Sciences | 3 | 2% |
| Other | 8 | 6% |
| Unknown | 30 | 23% |
Attention Score in Context
This research output has an Altmetric Attention Score of 6. 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 26 October 2023.
All research outputs
#6,310,110
of 25,611,630 outputs
Outputs from Machine Learning
#212
of 1,250 outputs
Outputs of similar age
#44,802
of 186,114 outputs
Outputs of similar age from Machine Learning
#2
of 10 outputs
Altmetric has tracked 25,611,630 research outputs across all sources so far. Compared to these this one has done well and is in the 75th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,250 research outputs from this source. They receive a mean Attention Score of 4.2. This one has done well, scoring higher than 83% 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 186,114 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 75% of its contemporaries.
We're also able to compare this research output to 10 others from the same source and published within six weeks on either side of this one. This one has scored higher than 8 of them.