
Behavior Constraining in Weight Space for Offline Reinforcement Learning
In offline reinforcement learning, a policy needs to be learned from a s...
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Overcoming Model Bias for Robust Offline Deep Reinforcement Learning
Stateoftheart reinforcement learning algorithms mostly rely on being ...
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Generating Interpretable Fuzzy Controllers using Particle Swarm Optimization and Genetic Programming
Autonomously training interpretable control strategies, called policies,...
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Interpretable Policies for Reinforcement Learning by Genetic Programming
The search for interpretable reinforcement learning policies is of high ...
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Sensitivity Analysis for Predictive Uncertainty in Bayesian Neural Networks
We derive a novel sensitivity analysis of input variables for predictive...
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Decomposition of Uncertainty for Active Learning and Reliable Reinforcement Learning in Stochastic Systems
Bayesian neural networks (BNNs) with latent variables are probabilistic ...
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A Benchmark Environment Motivated by Industrial Control Problems
In the research area of reinforcement learning (RL), frequently novel an...
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Uncertainty Decomposition in Bayesian Neural Networks with Latent Variables
Bayesian neural networks (BNNs) with latent variables are probabilistic ...
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Batch Reinforcement Learning on the Industrial Benchmark: First Experiences
The Particle Swarm Optimization Policy (PSOP) has been recently introdu...
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Particle Swarm Optimization for Generating Interpretable Fuzzy Reinforcement Learning Policies
Fuzzy controllers are efficient and interpretable system controllers for...
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Learning and Policy Search in Stochastic Dynamical Systems with Bayesian Neural Networks
We present an algorithm for modelbased reinforcement learning that comb...
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Steffen Udluft
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Head of research team Learning Systems, Researcher Reinforcement Learning, Corporate Technology Munich at Siemens