1 citations · 1 across the 1 of their papers we have counts for
4 papers
Trustworthy AI for Process Automation on a Chylla-Haase Polymerization Reactor
Daniel Hein, Daniel Labisch
In this paper, genetic programming reinforcement learning (GPRL) is utilized to generate human-interpretable control policies for a Chylla-Haase polymerization reactor. Such contin…
Behavior Constraining in Weight Space for Offline Reinforcement Learning
Phillip Swazinna, Steffen Udluft, Daniel Hein +1
In offline reinforcement learning, a policy needs to be learned from a single pre-collected dataset. Typically, policies are thus regularized during training to behave similarly to…
Interpretable Control by Reinforcement Learning
Daniel Hein, Steffen Limmer, Thomas A. Runkler
In this paper, three recently introduced reinforcement learning (RL) methods are used to generate human-interpretable policies for the cart-pole balancing benchmark. The novel RL m…
Generating Interpretable Fuzzy Controllers using Particle Swarm Optimization and Genetic Programming
Daniel Hein, Steffen Udluft, Thomas A. Runkler
Autonomously training interpretable control strategies, called policies, using pre-existing plant trajectory data is of great interest in industrial applications. Fuzzy controllers…