2 citations · 7 across the 15 of their papers we have counts for
3 papers · 1 filter
Reward Machine Inference for Robotic Manipulation
Mattijs Baert, Sam Leroux, Pieter Simoens
Learning from Demonstrations (LfD) and Reinforcement Learning (RL) have enabled robot agents to accomplish complex tasks. Reward Machines (RMs) enhance RL's capability to train pol…
Learning Task Specifications from Demonstrations as Probabilistic Automata
Mattijs Baert, Sam Leroux, Pieter Simoens
Specifying tasks for robotic systems traditionally requires coding expertise, deep domain knowledge, and significant time investment. While learning from demonstration offers a pro…
Mitigating Bias Using Model-Agnostic Data Attribution
Sander De Coninck, Sam Leroux, Pieter Simoens
Mitigating bias in machine learning models is a critical endeavor for ensuring fairness and equity. In this paper, we propose a novel approach to address bias by leveraging pixel i…