Contrastive Meta-Learning for Partially Observable Few-Shot Learning. - Adam Jelley; Amos J. Storkey; Antreas Antoniou; Sam Devlin (ICLR, 2023)

Diffusion for World Modeling: Visual Details Matter in Atari. - Eloi Alonso; Adam Jelley; Vincent Micheli; Anssi Kanervisto; Amos J. Storkey; Tim Pearce; François Fleuret (NeurIPS, 2024)

Planning to Go Out-of-Distribution in Offline-to-Online Reinforcement Learning. - Trevor McInroe; Adam Jelley; Stefano V. Albrecht; Amos J. Storkey (RLJ, 2024)

Aligning Agents like Large Language Models. - Adam Jelley; Yuhan Cao 001; David Bignell; Sam Devlin; Tabish Rashid (CoRR, 2024)

Efficient Offline Reinforcement Learning: The Critic is Critical. - Adam Jelley; Trevor McInroe; Sam Devlin; Amos J. Storkey (CoRR, 2024)

LLM-Personalize: Aligning LLM Planners with Human Preferences via Reinforced Self-Training for Housekeeping Robots. - Dongge Han; Trevor McInroe; Adam Jelley; Stefano V. Albrecht; Peter Bell 001; Amos J. Storkey (COLING, 2025)

Objects matter: object-centric world models improve reinforcement learning in visually complex environments. - Weipu Zhang; Adam Jelley; Trevor McInroe; Amos J. Storkey (CoRR, 2025)