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pro vyhledávání: '"Hentschel, Alexander"'
Elastic gridshells are advanced free-form structures enabling curved target shapes and material-efficient large spans. This paper focuses on a novel type of gridshells recently proposed employing a scissor-like deployment mechanism. While recent form
Externí odkaz:
http://arxiv.org/abs/2312.17181
Autor:
Hentschel, Alexander
Die zunehmende Integration von Aspekten der Innen- und Außenluftströmung in den architektonischen Entwurf und die Optimierung von Bauwerken erfordert ein grundlegendes und anschauliches Verständnis von Strömungsphäno-menen. Nahezu alle theoretis
Externí odkaz:
http://tuprints.ulb.tu-darmstadt.de/349/1/DISS_AH.pdf
Autor:
Hentschel, Alexander, Hassanzadeh-Nazarabadi, Yahya, Seraj, Ramtin, Shirley, Dieter, Lafrance, Layne
Most current blockchains require all full nodes to execute all tasks limits the throughput of existing blockchains, which are well documented and among the most significant hurdles for the widespread adoption of decentralized technology. This paper e
Externí odkaz:
http://arxiv.org/abs/2002.07403
Throughput limitations of existing blockchain architectures are well documented and are one of the most significant hurdles for their wide-spread adoption. In our previous proof-of-concept work, we have shown that separating computation from consensu
Externí odkaz:
http://arxiv.org/abs/1909.05832
Throughput limitations of existing blockchain architectures are one of the most significant hurdles for their wide-spread adoption. Attempts to address this challenge include layer-2 solutions, such as Bitcoin's Lightning or Ethereum's Plasma network
Externí odkaz:
http://arxiv.org/abs/1909.05821
Autor:
Hein, Daniel, Depeweg, Stefan, Tokic, Michel, Udluft, Steffen, Hentschel, Alexander, Runkler, Thomas A., Sterzing, Volkmar
Publikováno v:
2017 IEEE Symposium Series on Computational Intelligence (SSCI)
In the research area of reinforcement learning (RL), frequently novel and promising methods are developed and introduced to the RL community. However, although many researchers are keen to apply their methods on real-world problems, implementing such
Externí odkaz:
http://arxiv.org/abs/1709.09480
Autor:
Hein, Daniel, Udluft, Steffen, Tokic, Michel, Hentschel, Alexander, Runkler, Thomas A., Sterzing, Volkmar
Publikováno v:
2017 International Joint Conference on Neural Networks (IJCNN), Anchorage, AK, 2017, pp. 4214-4221
The Particle Swarm Optimization Policy (PSO-P) has been recently introduced and proven to produce remarkable results on interacting with academic reinforcement learning benchmarks in an off-policy, batch-based setting. To further investigate the prop
Externí odkaz:
http://arxiv.org/abs/1705.07262
Publikováno v:
Engineering Applications of Artificial Intelligence, Volume 65C, October 2017, Pages 87-98
Fuzzy controllers are efficient and interpretable system controllers for continuous state and action spaces. To date, such controllers have been constructed manually or trained automatically either using expert-generated problem-specific cost functio
Externí odkaz:
http://arxiv.org/abs/1610.05984
A novel reinforcement learning benchmark, called Industrial Benchmark, is introduced. The Industrial Benchmark aims at being be realistic in the sense, that it includes a variety of aspects that we found to be vital in industrial applications. It is
Externí odkaz:
http://arxiv.org/abs/1610.03793
Publikováno v:
A. Hentschel and B. C. Sanders, An efficient algorithm for optimizing adaptive quantum metrology processes, Physical Review Letters 107(23): 233601 (4 pp.), 30 November 2011
Quantum-enhanced metrology infers an unknown quantity with accuracy beyond the standard quantum limit (SQL). Feedback-based metrological techniques are promising for beating the SQL but devising the feedback procedures is difficult and inefficient. H
Externí odkaz:
http://arxiv.org/abs/1104.3844