Name
Title | ||
|---|---|---|
Efficient exploration in reinforcement learning-based cognitive radio spectrum sharing. |
Abstract | ||
|---|---|---|
This study introduces two novel approaches, pre-partitioning and weight-driven exploration, to enable an efficient learning process in the context of cognitive radio. Learning efficiency is crucial when applying reinforcement learning to cognitive radio since cognitive radio users will cause a higher level of disturbance in the exploration phase. Careful control of the tradeoff between exploration... |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1049/iet-com.2010.0258 | IET Communications |
Keywords | Field | DocType |
cognitive radio,learning (artificial intelligence) | Software-defined radio,Artificial intelligence,Spectrum sharing,Shared resource,Action selection,Radio spectrum,Mathematics,Cognitive radio,Partition method,Reinforcement learning | Journal |
Volume | Issue | ISSN |
5 | 10 | 1751-8628 |
Citations | PageRank | References |
24 | 1.12 | 12 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Tao Jiang | 1 | 57 | 5.24 |
| David Grace | 2 | 281 | 35.65 |
| Paul D. Mitchell | 3 | 188 | 25.21 |