4 papers
Ergodicity in reinforcement learning
Dominik Baumann, Erfaun Noorani, Arsenii Mustafin +5
In reinforcement learning, we typically aim to optimize the expected value of the sum of rewards an agent collects over a trajectory. However, if the process generating these rewar…
Model-Agnostic Solutions for Deep Reinforcement Learning in Non-Ergodic Contexts
Bert Verbruggen, Arne Vanhoyweghen, Vincent Ginis
Reinforcement Learning (RL) remains a central optimisation framework in machine learning. Although RL agents can converge to optimal solutions, the definition of ``optimality'' dep…
Metro 3 in Brussels under uncertainty: scenario-based public transport accessibility analysis
Brecht Verbeken, Arne Vanhoyweghen, Vincent Ginis
Metro Line 3 in Brussels is one of Europe's most debated infrastructure projects, marked by escalating costs, delays, and uncertainty over completion. Yet no public accessibility a…
Early evidence of how LLMs outperform traditional systems on OCR/HTR tasks for historical records
Seorin Kim, Julien Baudru, Wouter Ryckbosch +2
We explore the ability of two LLMs -- GPT-4o and Claude Sonnet 3.5 -- to transcribe historical handwritten documents in a tabular format and compare their performance to traditiona…