2 citations · 5 across the 3 of their papers we have counts for
3 papers
Deep reinforcement learning uncovers processes for separating azeotropic mixtures without prior knowledge
Quirin Göttl, Jonathan Pirnay, Jakob Burger +1
Process synthesis in chemical engineering is a complex planning problem due to vast search spaces, continuous parameters and the need for generalization. Deep reinforcement learnin…
Policy-Based Self-Competition for Planning Problems
Jonathan Pirnay, Quirin Göttl, Jakob Burger +1
AlphaZero-type algorithms may stop improving on single-player tasks in case the value network guiding the tree search is unable to approximate the outcome of an episode sufficientl…
Convex Envelope Method for determining liquid multi-phase equilibria in systems with arbitrary number of components
Quirin Göttl, Jonathan Pirnay, Dominik G. Grimm +1
The determination of liquid phase equilibria plays an important role in chemical process simulation. This work presents a generalization of an approach called the convex envelope m…