Publications

MaestroMotif: Skill Design from Artificial Intelligence Feedback
Martin Klissarov, Mikael Henaff, Roberta Raileanu, Shagun Sodhani, Pascal Vincent, Amy Zhang, Pierre-Luc Bacon, Doina Precup, Marlos C Machado*, Pierluca D'Oro*
ICLR (oral) , 2025.

Motif: Intrinsic Motivation from Artificial Intelligence Feedback
Martin Klissarov*, Pierluca D’Oro*, Shagun Sodhani, Roberta Raileanu, Pierre-Luc Bacon, Pascal Vincent, Amy Zhang, Mikael Henaff
ICLR, 2024.

Sample-Efficient Reinforcement Learning by Breaking the Replay Ratio Barrier
Pierluca D'Oro*, Max Schwarzer*, Evgenii Nikishin, Pierre-Luc Bacon, Marc G. Bellemare, Aaron Courville
ICLR (oral), 2023.

The Primacy Bias in Deep Reinforcement Learning
Evgenii Nikishin*, Max Schwarzer*, Pierluca D'Oro*, Pierre-Luc Bacon, Aaron Courville
ICML, 2022.

Policy Optimization in a Noisy Neighborhood: On Return Landscapes in Continuous Control
Nate Rahn*, Pierluca D'Oro*, Harley Wiltzer, Pierre-Luc Bacon, Marc G. Bellemare
NeurIPS, 2023.

Do Transformer World Models Give Better Policy Gradients?
Michel Ma*, Tianwei Ni, Clement Gehring, Pierluca D'Oro*, Pierre-Luc Bacon
ICML, 2024.

How to Learn a Useful Critic? Model-based Action-Gradient-Estimator Policy Optimization
Pierluca D'Oro, Wojciech Jaśkowski
NeurIPS, 2020.

Gradient-Aware Model-based Policy Search
Pierluca D'Oro*, Alberto Maria Metelli*, Andrea Tirinzoni, Matteo Papini, Marcello Restelli
AAAI, 2020.