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Dagstuhl-Seminar — Resilience and Antifragility of Autonomous Systems
28. Apr 2024 - 03. Mai 2024 • Schloss Dagstuhl, Wadern, Deutschland
Veranstalter:
Schloss Dagstuhl - Leibniz-Zentrum für Informatik
Zusammenfassung:
This Dagstuhl Seminar aims to unify the international research on resilient and antifragile autonomous systems (RAAS), leading to faster scientific advancements and industrial adoption. To that end, the seminar wants to bring together leading researchers and practitioners with expertise in autonomous system resilience, antifragility, safety, and ethics from disciplines including Computer Science, Computational Biology, and Ethics, to share and discuss each other’s understanding of, methods for, and open challenges related to RAAS.
Themen:
resilience, antifragility, autonomous systems, AI, safety, ethics and assurance of autonomous systems
Eintrags-ID:
1589779
2
Dagstuhl-Seminar — Causal Inference for Spatial Data Analytics
12. Mai 2024 - 17. Mai 2024 • Schloss Dagstuhl, Wadern, Deutschland
Veranstalter:
Schloss Dagstuhl - Leibniz-Zentrum für Informatik
Zusammenfassung:
The ability to identify causal relationships in spatial data is increasingly important for designing effective policy interventions in environmental science, epidemiology, urban planning, and traffic management. Current spatial data analytic methods rely mainly on descriptive and predictive methods that lack explicit causal models. Spatial causal inference offers a promising solution to address this challenge by extending causal inference methodologies to spatial domains. However, this translation is challenging due to spatial effects that violate fundamental assumptions of causal inference. Spatial causal inference is therefore still in its infancy, and there is a pressing need to accelerate its theoretical development and support its adoption with a well-grounded methodological toolset. This requires an interdisciplinary exchange of ideas, as researchers in different fields, such as environmental sciences, spatial statistics, theoretical GIScience, and machine learning, are making significant but disparate efforts in the foundations of spatial causal inference. To address these challenges, we convene the first Dagstuhl Seminar on Causal Inference for Spatial Data Analytics.
Eintrags-ID:
1589716
3
Dagstuhl-Seminar — Theory of Randomized Optimization Heuristics
30. Jun 2024 - 05. Jul 2024 • Schloss Dagstuhl, Wadern, Deutschland
Veranstalter:
Schloss Dagstuhl - Leibniz-Zentrum für Informatik
Zusammenfassung:
Randomized optimization heuristics (ROHs) are general-purpose solvers that are frequently applied for discrete or continuous optimization when other classes of solvers fail or are not applicable. Typical examples of ROHs include genetic algorithms, evolution strategies, and estimation-of-distribution algorithms (EDAs). Since ROHs are not designed with a proof or analysis in mind, their theoretical analysis is a particularly challenging endeavor. Yet, their practical success, extremely wide applicability, and growing relevance in many domains in industry and academic research push for progress in their understanding. This Dagstuhl Seminar is part of a very successful Dagstuhl Seminar series with the goal of driving this research area forward.
Eintrags-ID:
1566156


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Stand vom 27. November 2023