Automated Personnel Scheduling with Reinforcement Learning and Graph Neural Networks. - Benjamin Platten; Matthew Macfarlane; David Graus; Sepideh Mesbah (HR@RecSys, 2022)

A practical guide to multi-objective reinforcement learning and planning. - Conor F. Hayes; Roxana Radulescu; Eugenio Bargiacchi; Johan Källström; Matthew Macfarlane; Mathieu Reymond; Timothy Verstraeten; Luisa M. Zintgraf; Richard Dazeley; Fredrik Heintz; Enda Howley; Athirai A. Irissappane; et al. (Auton. Agents Multi Agent Syst., 2022)

A Brief Guide to Multi-Objective Reinforcement Learning and Planning. - Conor F. Hayes; Roxana Radulescu; Eugenio Bargiacchi; Johan Källström; Matthew Macfarlane; Mathieu Reymond; Timothy Verstraeten; Luisa M. Zintgraf; Richard Dazeley; Fredrik Heintz; Enda Howley; Athirai A. Irissappane; et al. (AAMAS, 2023)

Jumanji: a Diverse Suite of Scalable Reinforcement Learning Environments in JAX. - Clément Bonnet; Daniel Luo; Donal Byrne; Shikha Surana; Sasha Abramowitz; Paul Duckworth; Vincent Coyette; Laurence Illing Midgley; Elshadai Tegegn; Tristan Kalloniatis; Omayma Mahjoub; Matthew Macfarlane; et al. (ICLR, 2024)

SPO: Sequential Monte Carlo Policy Optimisation. - Matthew Macfarlane; Edan Toledo; Donal Byrne; Paul Duckworth; Alexandre Laterre (NeurIPS, 2024)

SMX: Sequential Monte Carlo Planning for Expert Iteration. - Matthew V. Macfarlane; Edan Toledo; Donal Byrne; Siddarth Singh; Paul Duckworth; Alexandre Laterre (CoRR, 2024)

Searching Latent Program Spaces. - Clément Bonnet; Matthew V. Macfarlane (CoRR, 2024)