1 citations · 1 across the 4 of their papers we have counts for
5 papers
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…
Learning Safety Constraints From Demonstration Using One-Class Decision Trees
Mattijs Baert, Sam Leroux, Pieter Simoens
The alignment of autonomous agents with human values is a pivotal challenge when deploying these agents within physical environments, where safety is an important concern. However,…
Maximum Causal Entropy Inverse Constrained Reinforcement Learning
Mattijs Baert, Pietro Mazzaglia, Sam Leroux +1
When deploying artificial agents in real-world environments where they interact with humans, it is crucial that their behavior is aligned with the values, social norms or other req…
Intelligent Frame Selection as a Privacy-Friendlier Alternative to Face Recognition
Mattijs Baert, Sam Leroux, Pieter Simoens
The widespread deployment of surveillance cameras for facial recognition gives rise to many privacy concerns. This study proposes a privacy-friendly alternative to large scale faci…