18 citations · 33 across the 5 of their papers we have counts for
6 papers
Reinforcement Learning in Conflicting Environments for Autonomous Vehicles
Dominik Meyer, Johannes Feldmaier, Hao Shen
In this work, we investigate the application of Reinforcement Learning to two well known decision dilemmas, namely Newcomb's Problem and Prisoner's Dilemma. These problems are exem…
Regularized Gradient Temporal-Difference Learning
Dominik Meyer, Hao Shen, Klaus Diepold
In this paper, we study the Temporal Difference (TD) learning with linear value function approximation. It is well known that most TD learning algorithms are unstable with linear f…
Optimal Water Heater Control in Smart Home Environments
Christoph Passenberg, Dominik Meyer, Johannes Feldmaier +1
In this work, we develop an optimal water heater control method for a smart home environment. It is important to notice that unlike battery storage systems, energy flow in a water…
Monitoring and Prediction in Smart Energy Systems via Multi-timescale Nexting
Johannes Feldmaier, Dominik Meyer, Hao Shen +1
Reliable prediction of system status is a highly demanded functionality of smart energy systems, which can enable users or human operators to react quickly to potential future syst…
Texture Retrieval via the Scattering Transform
Alexander Sagel, Dominik Meyer, Hao Shen
This work studies the problem of content-based image retrieval, specifically, texture retrieval. It focuses on feature extraction and similarity measure for texture images. Our app…
Optimal uncertainty quantification for legacy data observations of Lipschitz functions
T. J. Sullivan, M. McKerns, D. Meyer +3
We consider the problem of providing optimal uncertainty quantification (UQ) --- and hence rigorous certification --- for partially-observed functions. We present a UQ framework wi…