Project: Research Programme Artificial Intelligence - 2022
2022-01-01 – 2022-12-31
- Abstract
We are not always aware of it, but artificial intelligence (AI) is gradually penetrating all areas of our lives and our economy. How should we deal with it? Five Flemish universities and five Flemish research institutes - KU Leuven, Universiteit Antwerpen, Universiteit Gent, Universiteit Hasselt, Vrije Universiteit Brussel, Flanders Make, Sirris, VIB, VITO and imec - form a consortium for strategic basic research in AI. The Flemish AI Research Programme is funded by the Department of Economy, Science and Innovation. It is part of a broader policy agenda that also stimulates the use of AI by businesses and organisations, and that focuses on awareness, training and ethical framing.
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- Conference Paper
- C1
- open access
Optimization of plasma-assisted surface treatment for adhesive bonding via artificial intelligence
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- Journal Article
- A1
- open access
Fuzzy relational Galois connections between fuzzy transitive digraphs
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- Journal Article
- A1
- open access
Features for the 0-1 knapsack problem based on inclusionwise maximal solutions
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- Journal Article
- A1
- open access
Optimizing cascaded control of mechatronic systems through constrained residual reinforcement learning
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- Journal Article
- A1
- open access
Exploring search space trees using an adapted version of Monte Carlo tree search for combinatorial optimization problems
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Personalised socially assistive robot for cardiac rehabilitation : critical reflections on long-term interactions in the real world
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- Journal Article
- A1
- open access
Bi-objective Bayesian optimization of engineering problems with cheap and expensive cost functions
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Deep-learning-based step detection and step length estimation with a handheld IMU
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- Journal Article
- A1
- open access
Optimising predictive models to prioritise viral discovery in zoonotic reservoirs
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- Journal Article
- A2
- open access
Seasonal prediction of Horn of Africa long rains using machine learning : the pitfalls of preselecting correlated predictors