Online Learning of non-Markovian Reward Models
G. Rens, J.-F. Raskin, R. Reynouard and G. Marra, ICAART 2021, pdf
CV
Education
- B.S. in Computer Science, Université Libre de Bruxelles, Belgium, 2019
- M.S. in Computer Science, Université Libre de Bruxelles, Belgium, 2020
- Ph.D in Computer Science, Reykjavik University, Iceland, 2023
Publications
Active Learning of Markov Decision Processes using Baum-Welch algorithm
G. Bacci, A. Ingólfsdóttir, K. Larsen, R. Reynouard, ICMLA 2021, pdf
Jajapy: a learning library for stochastic models
R. Reynouard, G. Bacci, A. Ingólfsdóttir, QEST 2023, pdf
A MM Algorithm to Estimate Parameters in Continuous-time Markov Chains
G. Bacci, A. Ingólfsdóttir, K. Larsen, R. Reynouard, QEST 2023, pdf
On learning stochastic models: from theory to practice
R. Reynouard, PhD Thesis 2023, pdf
Tools
Jajapy
Python, 2022, link
Research activities
Member of the Artifact Evaluation Committee
QEST 2023, website
Member of the Artifact Evaluation Committee
QEST 2024, website
Languages
- French (native)
- English (professional profeciency)
Skills
- Python
- Theory of Machine Learning
- PyTorch
- Markov models