| dc.contributor.author | Christensen, Sören | |
| dc.contributor.author | Tomforde, Sven | |
| dc.date | 2022-08-01 | |
| dc.date.accessioned | 2022-09-09T12:40:19Z | |
| dc.date.available | 2022-09-09T12:40:19Z | |
| dc.date.issued | 2022 | |
| dc.identifier.issn | 1432-122X | |
| dc.identifier.uri | http://dx.doi.org/10.1007/s00287-022-01468-x | |
| dc.identifier.uri | http://dl.gi.de/handle/20.500.12116/39365 | |
| dc.description.abstract | We propose to establish a research direction based on Reinforcement Learning in the scope of Cross Domain Fusion. More precisely, we combine the algorithmic approach of evolutionary rule-based Reinforcement Learning with the efficiency and performance of Deep Reinforcement Learning, while simultaneously developing a sound mathematical foundation. A possible scenario is traffic control in urban regions. | de |
| dc.publisher | Springer | |
| dc.relation.ispartof | Informatik Spektrum: Vol. 45, No. 4 | |
| dc.relation.ispartofseries | Informatik Spektrum | |
| dc.title | Reinforcement learning as a basis for cross domain fusion of heterogeneous data | de |
| dc.type | Text/Journal Article | |
| mci.reference.pages | 214-217 | |
| dc.identifier.doi | 10.1007/s00287-022-01468-x | |