Pilar von Pilchau, Wenzel
22  Ergebnisse:
Personensuche X
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2

Deep Q-Network Updates for the Full Action-Space Utilizing ..:

, In: 2023 International Joint Conference on Neural Networks (IJCNN),
 
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3

Application of Uncertainty-Aware Sensor Fusion in Physical ..:

, In: 2022 IEEE International Instrumentation and Measurement Technology Conference (I2MTC),
 
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4

Semi-model-Based Reinforcement Learning in Organic Computin..:

, In: Lecture Notes in Computer Science; Architecture of Computing Systems,
 
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8

Interpolation assisted deep reinforcement learning:

Baron Pilar von Pilchau, Wenzel
https://opus.bibliothek.uni-augsburg.de/opus4/frontdoor/index/index/docId/111814.  , 2024
 
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10

Interpolated experience replay for continuous environments:

Baron Pilar von Pilchau, Wenzel ; Stein, Anthony ; Hähner, Jörg
https://opus.bibliothek.uni-augsburg.de/opus4/frontdoor/index/index/docId/99989.  , 2022
 
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11

Harmonization of heterogeneous asset administration shells:

Koutrakis, Nikolaos-Stefanos ; Gowtham, Varun ; Baron Pilar von Pilchau, Wenzel...
https://opus.bibliothek.uni-augsburg.de/opus4/frontdoor/index/index/docId/100307.  , 2022
 
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13

Synthetic experiences for accelerating DQN performance in d..:

Baron Pilar von Pilchau, Wenzel ; Stein, Anthony ; Hähner, Jörg
https://opus.bibliothek.uni-augsburg.de/opus4/frontdoor/index/index/docId/89080.  , 2021
 
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15

Bootstrapping a DQN replay memory with synthetic experience:

Baron Pilar von Pilchau, Wenzel ; Stein, Anthony ; Hähner, Jörg
https://opus.bibliothek.uni-augsburg.de/opus4/frontdoor/index/index/docId/82480.  , 2020
 
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