7 citations · 12 across the 6 of their papers we have counts for
5 papers · 1 filter
Reusable Test Suites for Reinforcement Learning
Jørn Eirik Betten, Quentin Mazouni, Dennis Gross +2
Reinforcement learning (RL) agents show great promise in solving sequential decision-making tasks. However, validating the reliability and performance of the agent policies' behavi…
Prompting for Performance: Exploring LLMs for Configuring Software
Helge Spieker, Théo Matricon, Nassim Belmecheri +7
Software systems usually provide numerous configuration options that can affect performance metrics such as execution time, memory usage, binary size, or bitrate. On the one hand,…
Policy Testing with MDPFuzz (Replicability Study)
Quentin Mazouni, Helge Spieker, Arnaud Gotlieb +1
In recent years, following tremendous achievements in Reinforcement Learning, a great deal of interest has been devoted to ML models for sequential decision-making. Together with t…
Testing for Fault Diversity in Reinforcement Learning
Quentin Mazouni, Helge Spieker, Arnaud Gotlieb +1
Reinforcement Learning is the premier technique to approach sequential decision problems, including complex tasks such as driving cars and landing spacecraft. Among the software va…
A Review of Validation and Verification of Neural Network-based Policies for Sequential Decision Making
Q. Mazouni, H. Spieker, A. Gotlieb +1
In sequential decision making, neural networks (NNs) are nowadays commonly used to represent and learn the agent's policy. This area of application has implied new software quality…