New DFG Funding
We successfully attracted funding from the German Research Foundation (DFG) for the project “Reinforcement Learning for Automated Flowsheet Synthesis of Steady-State Processes”
New Publication in Nature Methods: The AIMe registry for artificial intelligence in biomedical research
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”.
New Publication: Automated Flowsheet Synthesis Using Hierarchical Reinforcement Learning
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.
New Funding: Glycoside Production
We successfully attracted funding for a new project from the Bavarian Ministry of Economic Affairs, Regional Development and Energy. More details will follow soon on our project page.
New Publication: Automated Process Synthesis Using Reinforcement Learning @ ESCAPE31
A novel method for automated flowsheet synthesis based on reinforcement learning (RL) is presented. Using the interaction with a process simulator as the learning environment, an agent is trained to solve the task of synthesizing process flowsheets without any heuristics or prior knowledge. The developed RL method models the task as a competitive two-player game that the agent plays against itself during training. The concept is proven to work along an example with a quaternary mixture that is processed using a reactor or distillation units.