7 papers
Emergent swimming strategies of a smart three-bead swimmer
Ruma Maity, Maximilian Huebl, Julian Lemmel +2
Low-Reynolds-number microswimmers have recently attracted much interest for their ubiquity in biology and their applications in biotechnology and medicine. However, a key obstacle…
Adaptive Control in Autonomous Driving via Real-Time Recurrent RL
Julian Lemmel, Felix Resch, Mónika Farsang +3
We study online fine-tuning of pretrained control policies for autonomous driving using Real-Time Recurrent Reinforcement Learning (RTRRL), a memory-efficient algorithm that update…
TubeDAgger: Reducing the Number of Expert Interventions with Stochastic Reach-Tubes
Julian Lemmel, Manuel Kranzl, Adam Lamine +3
Interactive Imitation Learning deals with training a novice policy from expert demonstrations in an online fashion. The established DAgger algorithm trains a robust novice policy b…
Online Fine-Tuning of Carbon Emission Predictions using Real-Time Recurrent Learning for State Space Models
Julian Lemmel, Manuel Kranzl, Adam Lamine +3
This paper introduces a new approach for fine-tuning the predictions of structured state space models (SSMs) at inference time using real-time recurrent learning. While SSMs are kn…
Real-Time Recurrent Reinforcement Learning
Julian Lemmel, Radu Grosu
We introduce a biologically plausible RL framework for solving tasks in partially observable Markov decision processes (POMDPs). The proposed algorithm combines three integral part…
A quantum-classical reinforcement learning model to play Atari games
Dominik Freinberger, Julian Lemmel, Radu Grosu +1
Recent advances in reinforcement learning have demonstrated the potential of quantum learning models based on parametrized quantum circuits as an alternative to deep learning model…