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pro vyhledávání: '"Ziemek, Robin"'
In adaptive systems, predictors are used to anticipate changes in the systems state or behavior that may require system adaption, e.g., changing its configuration or adjusting resource allocation. Therefore, the quality of predictors is crucial for t
Externí odkaz:
http://arxiv.org/abs/2412.11754
By combining two of the central paradigms of causality, namely counterfactual reasoning and probability-raising,we introduce a probabilistic notion of cause in Markov chains. Such a cause consists of finite executions of the probabilistic system afte
Externí odkaz:
https://tud.qucosa.de/id/qucosa%3A89234
https://tud.qucosa.de/api/qucosa%3A89234/attachment/ATT-0/
https://tud.qucosa.de/api/qucosa%3A89234/attachment/ATT-0/
Autor:
Ziemek, Robin
The complexity of modern computer and software systems still seems to grow exponentially, while the human user is widely left without explanations on how to understand these systems. One of the central tasks of current computer science therefore lies
Externí odkaz:
https://tud.qucosa.de/id/qucosa%3A93413
https://tud.qucosa.de/api/qucosa%3A93413/attachment/ATT-0/
https://tud.qucosa.de/api/qucosa%3A93413/attachment/ATT-0/
Publikováno v:
Logical Methods in Computer Science, Volume 20, Issue 1 (January 19, 2024) lmcs:10015
This work introduces a novel cause-effect relation in Markov decision processes using the probability-raising principle. Initially, sets of states as causes and effects are considered, which is subsequently extended to regular path properties as effe
Externí odkaz:
http://arxiv.org/abs/2209.02973
The purpose of this paper is to introduce a notion of causality in Markov decision processes based on the probability-raising principle and to analyze its algorithmic properties. The latter includes algorithms for checking cause-effect relationships
Externí odkaz:
http://arxiv.org/abs/2201.08768
Autor:
Baier, Christel, Dubslaff, Clemens, Funke, Florian, Jantsch, Simon, Majumdar, Rupak, Piribauer, Jakob, Ziemek, Robin
In view of the growing complexity of modern software architectures, formal models are increasingly used to understand why a system works the way it does, opposed to simply verifying that it behaves as intended. This paper surveys approaches to formal
Externí odkaz:
http://arxiv.org/abs/2105.09533
The paper studies a probabilistic notion of causes in Markov chains that relies on the counterfactuality principle and the probability-raising property. This notion is motivated by the use of causes for monitoring purposes where the aim is to detect
Externí odkaz:
http://arxiv.org/abs/2104.13604
Akademický článek
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Autor:
Baier, Christel, Dubslaff, Clemens, Funke, Florian, Jantsch, Simon, Majumdar, Rupak, Piribauer, Jakob, Ziemek, Robin
Publikováno v:
48th International Colloquium on Automata, Languages, and Programming
Leibniz International Proceedings in Informatics
Leibniz International Proceedings in Informatics
In view of the growing complexity of modern software architectures, formal models are increasingly used to understand why a system works the way it does, opposed to simply verifying that it behaves as intended. This paper surveys approaches to formal
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4823fab7a516e011afd9ea5f19c742d0
https://hdl.handle.net/21.11116/0000-0009-5525-E21.11116/0000-0009-5527-C
https://hdl.handle.net/21.11116/0000-0009-5525-E21.11116/0000-0009-5527-C