Zobrazeno 1 - 10
of 196
pro vyhledávání: '"Thomas A. Runkler"'
Publikováno v:
ACM Transactions on Internet Technology. 22:1-30
The Internet of Things (IoT) is revolutionizing the industry. Powered by pervasive embedded devices, the Industrial IoT (IIoT) provides a unique solution for retrieving and analyzing data near the source in real-time. Many emerging techniques, such a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f23c0d245b755c3fa4eb87fc35f48647
https://doi.org/10.1145/3510820
https://doi.org/10.1145/3510820
Autor:
Thomas A. Runkler
Publikováno v:
Soft Computing. 26:1-11
Decision making is a process that ranks or chooses subsets from given sets of options, for example, project proposals or machine tools, with high relevance in industry and economics. Each decision option may be associated with a degree of utility wit
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2cdfd85163d32f08062ae001cddb0195
https://doi.org/10.1007/s00500-021-06414-9
https://doi.org/10.1007/s00500-021-06414-9
Autor:
Thomas A. Runkler
Publikováno v:
2022 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f5c10c8437873ecbd1a62a9f12cf066b
https://doi.org/10.1109/fuzz-ieee55066.2022.9882586
https://doi.org/10.1109/fuzz-ieee55066.2022.9882586
Publikováno v:
Neurocomputing. 416:352-359
In this paper, we present a model-based reinforcement learning system where the transition model is treated in a Bayesian manner. The approach naturally lends itself to exploit expert knowledge by introducing priors to impose structure on the underly
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a43db64fc84186eccf2a727781cf64c2
https://doi.org/10.1016/j.neucom.2019.12.132
https://doi.org/10.1016/j.neucom.2019.12.132
Autor:
Thomas A. Runkler
Publikováno v:
Journal of Intelligent & Fuzzy Systems. 39:4027-4040
Fuzzy pairwise preferences are an important model to specify and process expert opinions. A fuzzy pairwise preference matrix contains degrees of preference of each option over each other option. Such degrees of preference are often numerically specif
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6ddcab8b29528d62c4962cc5c044b09d
https://doi.org/10.3233/jifs-200189
https://doi.org/10.3233/jifs-200189
Publikováno v:
IFAC-PapersOnLine. 53:8082-8089
In this paper, three recently introduced reinforcement learning (RL) methods are used to generate human-interpretable policies for the cart-pole balancing benchmark. The novel RL methods learn human-interpretable policies in the form of compact fuzzy
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7d45ccfdaf2c56f05caccd92f3d82b7a
https://doi.org/10.1016/j.ifacol.2020.12.2277
https://doi.org/10.1016/j.ifacol.2020.12.2277
Publikováno v:
The Semantic Web – ISWC 2022 ISBN: 9783031194320
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f08b8c702c2398649ed0bad6c8a7f063
https://doi.org/10.1007/978-3-031-19433-7_48
https://doi.org/10.1007/978-3-031-19433-7_48
Computing latent representations for graph-structured data is an ubiquitous learning task in many industrial and academic applications ranging from molecule synthetization to social network analysis and recommender systems. Knowledge graphs are among
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2f4929bda7a6407f2ce274639c334dcd
http://arxiv.org/abs/2109.10376
http://arxiv.org/abs/2109.10376
Autor:
Dickson Odhiambo Owuor, Edmond Odhiambo Menya, Joseph Onderi Orero, Anne Laurent, Thomas A. Runkler
Publikováno v:
International journal of machine learning and cybernetics
International journal of machine learning and cybernetics, Springer, 2021, 12, pp.2989-3009. ⟨10.1007/s13042-021-01390-w⟩
International journal of machine learning and cybernetics, Springer, 2021, 12, pp.2989-3009. ⟨10.1007/s13042-021-01390-w⟩
Gradual pattern extraction is a field in (KDD) Knowledge Discovery in Databases that maps correlations between attributes of a data set as gradual dependencies. A gradual dependency may take a form of "the more Attribute K , the less Attribute L". In
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c7dcec8062aa30c06c86906a3b6f52f0
https://hal-lirmm.ccsd.cnrs.fr/lirmm-03320956
https://hal-lirmm.ccsd.cnrs.fr/lirmm-03320956
Publikováno v:
IJCNN
In the last few years, several works have been proposed on Generative Adversarial Networks (GAN). At the same time, there is a lack of investigation on their evaluation and the few proposed evaluation methods have not yet been rigorously studied. By
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1069694dd46fc005a9eec6a0d1a0fbdd
https://doi.org/10.1109/ijcnn52387.2021.9534373
https://doi.org/10.1109/ijcnn52387.2021.9534373