5 citations · 6 across the 9 of their papers we have counts for
5 papers · 1 filter
Towards Generalisable Imitation Learning Through Conditioned Transition Estimation and Online Behaviour Alignment
Nathan Gavenski, Matteo Leonetti, Odinaldo Rodrigues
State-of-the-art imitation learning from observation methods (ILfO) have recently made significant progress, but they still have some limitations: they need action-based supervised…
Quantifying Generalisation in Imitation Learning
Nathan Gavenski, Odinaldo Rodrigues
Imitation learning benchmarks often lack sufficient variation between training and evaluation, limiting meaningful generalisation assessment. We introduce Labyrinth, a benchmarking…
Explorative Imitation Learning: A Path Signature Approach for Continuous Environments
Nathan Gavenski, Juarez Monteiro, Felipe Meneguzzi +2
Some imitation learning methods combine behavioural cloning with self-supervision to infer actions from state pairs. However, most rely on a large number of expert trajectories to…
A Survey of Imitation Learning Methods, Environments and Metrics
Nathan Gavenski, Felipe Meneguzzi, Michael Luck +1
Imitation learning is an approach in which an agent learns how to execute a task by trying to mimic how one or more teachers perform it. This learning approach offers a compromise…
Imitation Learning Datasets: A Toolkit For Creating Datasets, Training Agents and Benchmarking
Nathan Gavenski, Michael Luck, Odinaldo Rodrigues
Imitation learning field requires expert data to train agents in a task. Most often, this learning approach suffers from the absence of available data, which results in techniques…