Steffen Udluft

is this you? claim profile

0 followers
Siemens AG

Head of research team Learning Systems, Researcher Reinforcement Learning, Corporate Technology Munich at Siemens

Featured Co-authors

Finale Doshi-Velez
78 publications
José Miguel Hernández-Lobato
69 publications
Thomas Runkler
15 publications
Daniel Hein
8 publications
Thomas A. Runkler
6 publications
Stefan Depeweg
6 publications
Alexander Hentschel
6 publications
Michel Tokic
3 publications
Phillip Swazinna
2 publications
Volkmar Sterzing
2 publications

Behavior Constraining in Weight Space for Offline Reinforcement Learning

In offline reinforcement learning, a policy needs to be learned from a s...
07/12/2021 ∙ by Phillip Swazinna, et al. ∙ 0 ∙ share

read it
Overcoming Model Bias for Robust Offline Deep Reinforcement Learning

State-of-the-art reinforcement learning algorithms mostly rely on being ...
08/12/2020 ∙ by Phillip Swazinna, et al. ∙ 0 ∙ share

read it
Generating Interpretable Fuzzy Controllers using Particle Swarm Optimization and Genetic Programming

Autonomously training interpretable control strategies, called policies,...
04/29/2018 ∙ by Daniel Hein, et al. ∙ 0 ∙ share

read it
Interpretable Policies for Reinforcement Learning by Genetic Programming

The search for interpretable reinforcement learning policies is of high ...
12/12/2017 ∙ by Daniel Hein, et al. ∙ 0 ∙ share

read it
Sensitivity Analysis for Predictive Uncertainty in Bayesian Neural Networks

We derive a novel sensitivity analysis of input variables for predictive...
12/10/2017 ∙ by Stefan Depeweg, et al. ∙ 0 ∙ share

read it
Decomposition of Uncertainty for Active Learning and Reliable Reinforcement Learning in Stochastic Systems

Bayesian neural networks (BNNs) with latent variables are probabilistic ...
10/19/2017 ∙ by Stefan Depeweg, et al. ∙ 0 ∙ share

read it
A Benchmark Environment Motivated by Industrial Control Problems

In the research area of reinforcement learning (RL), frequently novel an...
09/27/2017 ∙ by Daniel Hein, et al. ∙ 0 ∙ share

read it
Uncertainty Decomposition in Bayesian Neural Networks with Latent Variables

Bayesian neural networks (BNNs) with latent variables are probabilistic ...
06/26/2017 ∙ by Stefan Depeweg, et al. ∙ 0 ∙ share

read it
Batch Reinforcement Learning on the Industrial Benchmark: First Experiences

The Particle Swarm Optimization Policy (PSO-P) has been recently introdu...
05/20/2017 ∙ by Daniel Hein, et al. ∙ 0 ∙ share

read it
Particle Swarm Optimization for Generating Interpretable Fuzzy Reinforcement Learning Policies

Fuzzy controllers are efficient and interpretable system controllers for...
10/19/2016 ∙ by Daniel Hein, et al. ∙ 0 ∙ share

read it
Learning and Policy Search in Stochastic Dynamical Systems with Bayesian Neural Networks

We present an algorithm for model-based reinforcement learning that comb...
05/23/2016 ∙ by Stefan Depeweg, et al. ∙ 0 ∙ share

read it