Daniel Hein | DeepAI

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Featured Co-authors

Thomas Runkler
27 publications
Steffen Udluft
19 publications
Simon Wiedemann
11 publications
Thomas A. Runkler
9 publications
Phillip Swazinna
7 publications
Stefan Depeweg
6 publications
Alexander Hentschel
6 publications
Steffen Limmer
4 publications
Michel Tokic
3 publications
Volkmar Sterzing
3 publications
Christian Mendl
1 publication

∙ 08/11/2023

Learning Control Policies for Variable Objectives from Offline Data

Offline reinforcement learning provides a viable approach to obtain adva...

0 Marc Weber, et al. ∙

∙ 06/09/2022

Quantum Policy Iteration via Amplitude Estimation and Grover Search – Towards Quantum Advantage for Reinforcement Learning

We present a full implementation and simulation of a novel quantum reinf...

0 Simon Wiedemann, et al. ∙

∙ 01/14/2022

Comparing Model-free and Model-based Algorithms for Offline Reinforcement Learning

Offline reinforcement learning (RL) Algorithms are often designed with e...

0 Phillip Swazinna, et al. ∙

∙ 08/30/2021

Trustworthy AI for Process Automation on a Chylla-Haase Polymerization Reactor

In this paper, genetic programming reinforcement learning (GPRL) is util...

0 Daniel Hein, et al. ∙

∙ 07/12/2021

Behavior Constraining in Weight Space for Offline Reinforcement Learning

In offline reinforcement learning, a policy needs to be learned from a s...

0 Phillip Swazinna, et al. ∙

∙ 07/20/2020

Interpretable Control by Reinforcement Learning

In this paper, three recently introduced reinforcement learning (RL) met...

0 Daniel Hein, et al. ∙

∙ 04/29/2018

Generating Interpretable Fuzzy Controllers using Particle Swarm Optimization and Genetic Programming

Autonomously training interpretable control strategies, called policies,...

0 Daniel Hein, et al. ∙

∙ 12/12/2017

Interpretable Policies for Reinforcement Learning by Genetic Programming

The search for interpretable reinforcement learning policies is of high ...

0 Daniel Hein, et al. ∙

∙ 09/27/2017

A Benchmark Environment Motivated by Industrial Control Problems

In the research area of reinforcement learning (RL), frequently novel an...

0 Daniel Hein, et al. ∙

∙ 05/20/2017

Batch Reinforcement Learning on the Industrial Benchmark: First Experiences

The Particle Swarm Optimization Policy (PSO-P) has been recently introdu...

0 Daniel Hein, et al. ∙

∙ 10/19/2016

Particle Swarm Optimization for Generating Interpretable Fuzzy Reinforcement Learning Policies

Fuzzy controllers are efficient and interpretable system controllers for...

0 Daniel Hein, et al. ∙

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