48 citations · 71 across the 10 of their papers we have counts for
3 papers · 1 filter
Generative Adversarial Learning from Deterministic Processes
Joris C. Kühl, Hanno Gottschalk
Physical AI is being successfully applied to data which does not follow the traditional paradigm of independent and identically distributed (i.i.d.) samples. In fact, physical AI i…
Robust Evolutionary Multi-Objective Network Architecture Search for Reinforcement Learning (EMNAS-RL)
Nihal Acharya Adde, Alexandra Gianzina, Hanno Gottschalk +1
This paper introduces Evolutionary Multi-Objective Network Architecture Search (EMNAS) for the first time to optimize neural network architectures in large-scale Reinforcement Lear…
Hyperparameter Optimization for Driving Strategies Based on Reinforcement Learning
Nihal Acharya Adde, Hanno Gottschalk, Andreas Ebert
This paper focuses on hyperparameter optimization for autonomous driving strategies based on Reinforcement Learning. We provide a detailed description of training the RL agent in a…