Reinforcement learning as a basis for cross domain fusion of heterogeneous data
Zusammenfassung
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.
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- BibTeX
Christensen, S. & Tomforde, S.,
(2022).
Reinforcement learning as a basis for cross domain fusion of heterogeneous data.
Informatik Spektrum: Vol. 45, No. 4.
Springer.
(S. 214-217).
DOI: 10.1007/s00287-022-01468-x
@article{mci/Christensen2022,
author = {Christensen, Sören AND Tomforde, Sven},
title = {Reinforcement learning as a basis for cross domain fusion of heterogeneous data},
journal = {Informatik Spektrum},
volume = {45},
number = {4},
year = {2022},
,
pages = { 214-217 } ,
doi = { 10.1007/s00287-022-01468-x }
}
author = {Christensen, Sören AND Tomforde, Sven},
title = {Reinforcement learning as a basis for cross domain fusion of heterogeneous data},
journal = {Informatik Spektrum},
volume = {45},
number = {4},
year = {2022},
,
pages = { 214-217 } ,
doi = { 10.1007/s00287-022-01468-x }
}
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Mehr Information
ISSN: 1432-122X
Datum: 2022
Typ: Text/Journal Article

