Action Branching Architectures for Deep Reinforcement Learning. - Arash Tavakoli; Fabio Pardo; Petar Kormushev (AAAI, 2018)

Time Limits in Reinforcement Learning. - Fabio Pardo; Arash Tavakoli; Vitaly Levdik; Petar Kormushev (ICML, 2018)

Goal-oriented Trajectories for Efficient Exploration. - Fabio Pardo; Vitaly Levdik; Petar Kormushev (CoRR, 2018)

Q-map: a Convolutional Approach for Goal-Oriented Reinforcement Learning. - Fabio Pardo; Vitaly Levdik; Petar Kormushev (CoRR, 2018)

Scaling All-Goals Updates in Reinforcement Learning Using Convolutional Neural Networks. - Fabio Pardo; Vitaly Levdik; Petar Kormushev (AAAI, 2020)

CoMic: Complementary Task Learning & Mimicry for Reusable Skills. - Leonard Hasenclever; Fabio Pardo; Raia Hadsell; Nicolas Heess; Josh Merel (ICML, 2020)

Tonic: A Deep Reinforcement Learning Library for Fast Prototyping and Benchmarking. - Fabio Pardo (CoRR, 2020)

Ivy: Templated Deep Learning for Inter-Framework Portability. - Daniel Lenton; Fabio Pardo; Fabian Falck; Stephen James; Ronald Clark (CoRR, 2021)

OstrichRL: A Musculoskeletal Ostrich Simulation to Study Bio-mechanical Locomotion. - Vittorio La Barbera; Fabio Pardo; Yuval Tassa; Monica Daley; Christopher Richards; Petar Kormushev; John R. Hutchinson (CoRR, 2021)

Vision-Language Models as a Source of Rewards. - Kate Baumli; Satinder Baveja; Feryal M. P. Behbahani; Harris Chan; Gheorghe Comanici; Sebastian Flennerhag; Maxime Gazeau; Kristian Holsheimer; Dan Horgan; Michael Laskin; Clare Lyle; Hussain Masoom; et al. (CoRR, 2023)

LMAct: A Benchmark for In-Context Imitation Learning with Long Multimodal Demonstrations. - Anian Ruoss; Fabio Pardo; Harris Chan; Bonnie Li; Volodymyr Mnih; Tim Genewein (CoRR, 2024)