You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output.
Click here to find out more.
Mendeley readers
| Chapter title |
Policy-Based Reinforcement Learning Approaches
|
|---|---|
| Chapter number | 10 |
| Book title |
Deep Reinforcement Learning
|
| Published by |
Springer, Singapore, January 2019
|
| DOI | 10.1007/978-981-13-8285-7_10 |
| Book ISBNs |
978-9-81-138284-0, 978-9-81-138285-7
|
| Authors |
Mohit Sewak |
Mendeley readers
The data shown below were compiled from readership statistics for 7 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 7 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 2 | 29% |
| Student > Bachelor | 1 | 14% |
| Unspecified | 1 | 14% |
| Unknown | 3 | 43% |
| Readers by discipline | Count | As % |
|---|---|---|
| Chemical Engineering | 1 | 14% |
| Unspecified | 1 | 14% |
| Computer Science | 1 | 14% |
| Engineering | 1 | 14% |
| Unknown | 3 | 43% |