Together with Computomics GmbH we successfully attracted funding from the Federal Ministry of Education and Research (BMBF) for our new project “CropML: New machine learning techniques for more accurate plant breeding by integrating heterogeneous external factors”.
We published a novel machine learning algorithm EVARS-GPR an EVent-triggered Augmented Refitting of Gaussian Process Regression for Seasonal Data. Florian presented the method at the German AI Conference. The talk can be found on youtube: https://youtu.be/jZ6hZNMa-TE
We successfully attracted funding from the German Research Foundation (DFG) for the project “Reinforcement Learning for Automated Flowsheet Synthesis of Steady-State Processes”
An international research team with participants from several universities including Prof. Dr. Dominik Grimm has proposed a standardized registry for artificial intelligence (AI) work in biomedicine to improve the reproducibility of results and create trust in the use of AI algorithms in biomedical research and, in the future, in everyday clinical practice. The scientists presented their proposal in the scientific journal “Nature Methods”.
Recently we showed that reinforcement learning can be used to automatically generate process flowsheets without heuristics or prior knowledge. For this purpose, SynGameZero, a novel two-player game has been developed. In this work we extend SynGameZero by structuring the agent’s actions in several hierarchy levels, which improves the approach in terms of scalability and allows the consideration of more sophisticated flowsheet problems. We successfully demonstrate the usability of our novel framework for the fully automated synthesis of an ethyl tert-butyl ether process.