Novelty Detection in Thermal Video. - Matthew Aitchison; Richard Green (IVCNZ, 2018)

Optimal Use of Experience in First Person Shooter Environments. - Matthew Aitchison (CoG, 2019)

Improving StarCraft II Player League Prediction with Macro-Level Features. - Yinheng Chen; Matthew Aitchison; Penny Sweetser (Australasian Conference on Artificial Intelligence, 2020)

Designing Curriculum for Deep Reinforcement Learning in StarCraft II. - Daniel Hao; Penny Sweetser; Matthew Aitchison (Australasian Conference on Artificial Intelligence, 2020)

Do Game Bots Dream of Electric Rewards?: The universality of intrinsic motivation. - Penny Sweetser; Matthew Aitchison (FDG, 2020)

Curriculum Generation and Sequencing for Deep Reinforcement Learning in StarCraft II. - Daniel Hao; Penny Sweetser; Matthew Aitchison (ACSW, 2022)

DNA: Proximal Policy Optimization with a Dual Network Architecture. - Matthew Aitchison; Penny Sweetser (NeurIPS, 2022)

Learning to Deceive in Multi-Agent Hidden Role Games. - Matthew Aitchison; Lyndon Benke; Penny Sweetser (CoRR, 2022)

An Agile New Research Framework for Hybrid Human-AI Teaming: Trust, Transparency, and Transferability. - Sabrina B. Caldwell; Penny Sweetser; Nicholas O'Donnell; Matthew James Knight; Matthew Aitchison; Tom Gedeon; Daniel Johnson 001; Margot Brereton; Marcus Gallagher; David Conroy (ACM Trans. Interact. Intell. Syst., 2022)

HiveMind: Learning to Play the Cooperative Chess Variant Bughouse with DNNs and MCTS. - Benjamin Woo; Penny Sweetser; Matthew Aitchison (CoG, 2023)

Atari-5: Distilling the Arcade Learning Environment down to Five Games. - Matthew Aitchison; Penny Sweetser; Marcus Hutter (ICML, 2023)

Self-Predictive Universal AI. - Elliot Catt; Jordi Grau-Moya; Marcus Hutter; Matthew Aitchison; Tim Genewein; Grégoire Delétang; Kevin Li; Joel Veness (NeurIPS, 2023)

Language Modeling Is Compression. - Grégoire Delétang; Anian Ruoss; Paul-Ambroise Duquenne; Elliot Catt; Tim Genewein; Christopher Mattern; Jordi Grau-Moya; Li Kevin Wenliang; Matthew Aitchison; Laurent Orseau; Marcus Hutter; Joel Veness (ICLR, 2024)

Learning Universal Predictors. - Jordi Grau-Moya; Tim Genewein; Marcus Hutter; Laurent Orseau; Grégoire Delétang; Elliot Catt; Anian Ruoss; Li Kevin Wenliang; Christopher Mattern; Matthew Aitchison; Joel Veness (ICML, 2024)

Distributional Bellman Operators over Mean Embeddings. - Li Kevin Wenliang; Grégoire Delétang; Matthew Aitchison; Marcus Hutter; Anian Ruoss; Arthur Gretton; Mark Rowland 001 (ICML, 2024)

Evaluating Frontier Models for Dangerous Capabilities. - Mary Phuong; Matthew Aitchison; Elliot Catt; Sarah Cogan; Alexandre Kaskasoli; Victoria Krakovna; David Lindner; Matthew Rahtz; Yannis Assael; Sarah Hodkinson; Heidi Howard; Tom Lieberum; et al. (CoRR, 2024)