39 citations · 63 across the 21 of their papers we have counts for
8 papers · 1 filter
Predictive Safety Shield for Dyna-Q Reinforcement Learning
Jin Pin, Krasowski Hanna, Vanneaux Elena
Obtaining safety guarantees for reinforcement learning is a major challenge to achieve applicability for real-world tasks. Safety shields extend standard reinforcement learning and…
Automata-Conditioned Cooperative Multi-Agent Reinforcement Learning
Beyazit Yalcinkaya, Marcell Vazquez-Chanlatte, Ameesh Shah +2
We study learning multi-task, multi-agent policies for cooperative, temporal objectives, under centralized training, decentralized execution. In this setting, using automata to rep…
pacSTL: PAC-Bounded Signal Temporal Logic from Data-Driven Reachability Analysis
Hanna Krasowski, Elizabeth Dietrich, Emir Cem Gezer +3
Signal Temporal Logic (STL) is an expressive language for specifying behaviors of dynamical systems from continuous signals. However, a limitation of standard STL is its inherently…
Falsification-driven reinforcement learning for maritime motion planning
Marlon Müller, Florian Finkeldei, Hanna Krasowski +2
Compliance with maritime traffic rules is essential for the safe operation of autonomous vessels, yet training reinforcement learning (RL) agents to adhere to them is challenging.…
STL-based Optimization of Biomolecular Neural Networks for Regression and Control
Eric Palanques-Tost, Hanna Krasowski, Murat Arcak +2
Biomolecular Neural Networks (BNNs), artificial neural networks with biologically synthesizable architectures, achieve universal function approximation capabilities beyond simple b…
Safe Reinforcement Learning using Action Projection: Safeguard the Policy or the Environment?
Hannah Markgraf, Shambhuraj Sawant, Hanna Krasowski +3
Projection-based safety filters, which modify unsafe actions by mapping them to the closest safe alternative, are widely used to enforce safety constraints in reinforcement learnin…
Learning to Drive by Imitating Surrounding Vehicles
Yasin Sonmez, Hanna Krasowski, Murat Arcak
Imitation learning is a promising approach for training autonomous vehicles (AV) to navigate complex traffic environments by mimicking expert driver behaviors. While existing imita…
Intelligent Sailing Model for Open Sea Navigation
Hanna Krasowski, Stefan Schärdinger, Murat Arcak +1
Autonomous vessels potentially enhance safety and reliability of seaborne trade. To facilitate the development of autonomous vessels, simulations are required to model realistic in…