Name
Abstract | ||
|---|---|---|
Classic theories of reinforcement learning and neuromodulation rely on reward prediction errors. A new machine learning technique relies on neuromodulatory signals that are optimized for specific tasks, which may lead to better AI and better explanations of neuroscience data. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1038/s42256-019-0053-0 | NATURE MACHINE INTELLIGENCE |
DocType | Volume | Issue |
Journal | 1 | 5 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
1 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Blake A. Richards | 1 | 0 | 0.34 |