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Mendeley readers
| Chapter title |
Policy Gradient
|
|---|---|
| Chapter number | 5 |
| Book title |
Deep Reinforcement Learning
|
| Published by |
Springer, Singapore, January 2020
|
| DOI | 10.1007/978-981-15-4095-0_5 |
| Book ISBNs |
978-9-81-154094-3, 978-9-81-154095-0
|
| Authors |
Ruitong Huang, Tianyang Yu, Zihan Ding, Shanghang Zhang, Huang, Ruitong, Yu, Tianyang, Ding, Zihan, Zhang, Shanghang |
Mendeley readers
The data shown below were compiled from readership statistics for 106 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Switzerland | 1 | <1% |
| Unknown | 105 | 99% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 22 | 21% |
| Student > Ph. D. Student | 20 | 19% |
| Researcher | 16 | 15% |
| Student > Bachelor | 7 | 7% |
| Student > Postgraduate | 6 | 6% |
| Other | 9 | 8% |
| Unknown | 26 | 25% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 40 | 38% |
| Engineering | 25 | 24% |
| Chemistry | 3 | 3% |
| Economics, Econometrics and Finance | 2 | 2% |
| Mathematics | 2 | 2% |
| Other | 5 | 5% |
| Unknown | 29 | 27% |