Counterfactual reasoning about intent for interactive navigation in dynamic environments. - Alejandro Bordallo; Fabio Previtali; Nantas Nardelli; Subramanian Ramamoorthy (IROS, 2015)

Playing Doom with SLAM-Augmented Deep Reinforcement Learning. - Shehroze Bhatti; Alban Desmaison; Ondrej Miksik; Nantas Nardelli; N. Siddharth 001; Philip H. S. Torr (CoRR, 2016)

TorchCraft: a Library for Machine Learning Research on Real-Time Strategy Games. - Gabriel Synnaeve; Nantas Nardelli; Alex Auvolat; Soumith Chintala; Timothée Lacroix; Zeming Lin; Florian Richoux; Nicolas Usunier (CoRR, 2016)

Stabilising Experience Replay for Deep Multi-Agent Reinforcement Learning. - Jakob N. Foerster; Nantas Nardelli; Gregory Farquhar; Triantafyllos Afouras; Philip H. S. Torr; Pushmeet Kohli; Shimon Whiteson (ICML, 2017)

Stabilising Experience Replay for Deep Multi-Agent Reinforcement Learning. - Jakob N. Foerster; Nantas Nardelli; Gregory Farquhar; Philip H. S. Torr; Pushmeet Kohli; Shimon Whiteson (CoRR, 2017)

Counterfactual Multi-Agent Policy Gradients. - Jakob N. Foerster; Gregory Farquhar; Triantafyllos Afouras; Nantas Nardelli; Shimon Whiteson (AAAI, 2018)

The StarCraft Multi-Agent Challenge. - Mikayel Samvelyan; Tabish Rashid; Christian Schröder de Witt; Gregory Farquhar; Nantas Nardelli; Tim G. J. Rudner; Chia-Man Hung; Philip H. S. Torr; Jakob N. Foerster; Shimon Whiteson (AAMAS, 2019)

Value Propagation Networks. - Nantas Nardelli; Gabriel Synnaeve; Zeming Lin; Pushmeet Kohli; Philip H. S. Torr; Nicolas Usunier (ICLR (Poster), 2019)

A Survey of Reinforcement Learning Informed by Natural Language. - Jelena Luketina; Nantas Nardelli; Gregory Farquhar; Jakob N. Foerster; Jacob Andreas; Edward Grefenstette; Shimon Whiteson; Tim Rocktäschel (IJCAI, 2019)

Multitask Soft Option Learning. - Maximilian Igl; Andrew Gambardella; Nantas Nardelli; N. Siddharth 001; Wendelin Böhmer; Shimon Whiteson (CoRR, 2019)

TorchBeast: A PyTorch Platform for Distributed RL. - Heinrich Küttler; Nantas Nardelli; Thibaut Lavril; Marco Selvatici; Viswanath Sivakumar; Tim Rocktäschel; Edward Grefenstette (CoRR, 2019)

MVFST-RL: An Asynchronous RL Framework for Congestion Control with Delayed Actions. - Viswanath Sivakumar; Tim Rocktäschel; Alexander H. Miller; Heinrich Küttler; Nantas Nardelli; Mike Rabbat; Joelle Pineau; Sebastian Riedel 001 (CoRR, 2019)

Lessons from reinforcement learning for biological representations of space. - Alexander Muryy; N. Siddharth 001; Nantas Nardelli; Andrew Glennerster; Philip H. S. Torr (CoRR, 2019)

The NetHack Learning Environment. - Heinrich Küttler; Nantas Nardelli; Alexander H. Miller; Roberta Raileanu; Marco Selvatici; Edward Grefenstette; Tim Rocktäschel (NeurIPS, 2020)

Multitask Soft Option Learning. - Maximilian Igl; Andrew Gambardella; Jinke He; Nantas Nardelli; N. Siddharth 001; Wendelin Boehmer; Shimon Whiteson (UAI, 2020)

Simulation-Based Inference for Global Health Decisions. - Christian Schröder de Witt; Bradley Gram-Hansen; Nantas Nardelli; Andrew Gambardella; Robert Zinkov; Puneet K. Dokania; N. Siddharth 001; Ana Belen Espinosa-Gonzalez; Ara Darzi; Philip H. S. Torr; Atilim Günes Baydin (CoRR, 2020)

WordCraft: An Environment for Benchmarking Commonsense Agents. - Minqi Jiang; Jelena Luketina; Nantas Nardelli; Pasquale Minervini; Philip H. S. Torr; Shimon Whiteson; Tim Rocktäschel (CoRR, 2020)

Insights From the NeurIPS 2021 NetHack Challenge. - Eric Hambro; Sharada P. Mohanty; Dmitrii Babaev; Minwoo Byeon; Dipam Chakraborty; Edward Grefenstette; Minqi Jiang; DaeJin Jo; Anssi Kanervisto; Jongmin Kim 006; Sungwoong Kim; Robert Kirk; et al. (NeurIPS (Competition and Demos), 2021)

Can Reinforcement Learning support policy makers? A preliminary study with Integrated Assessment Models. - Theodore Wolf; Nantas Nardelli; John Shawe-Taylor; María Pérez-Ortiz 001 (CoRR, 2023)