Generalised Discount Functions applied to a Monte-Carlo AI u Implementation. - Sean Lamont; John Aslanides; Jan Leike; Marcus Hutter (AAMAS, 2017)

Universal Reinforcement Learning Algorithms: Survey and Experiments. - John Aslanides; Jan Leike; Marcus Hutter (IJCAI, 2017)

AIXIjs: A Software Demo for General Reinforcement Learning. - John Aslanides (CoRR, 2017)

Generalised Discount Functions applied to a Monte-Carlo AImu Implementation. - Sean Lamont; John Aslanides; Jan Leike; Marcus Hutter (CoRR, 2017)

Randomized Prior Functions for Deep Reinforcement Learning. - Ian Osband; John Aslanides; Albin Cassirer (NeurIPS, 2018)

When to use parametric models in reinforcement learning? - Hado van Hasselt; Matteo Hessel; John Aslanides (NeurIPS, 2019)

TF-Replicator: Distributed Machine Learning for Researchers. - Peter Buchlovsky; David Budden; Dominik Grewe; Chris Jones; John Aslanides; Frederic Besse; Andy Brock; Aidan Clark; Sergio Gomez Colmenarejo; Aedan Pope; Fabio Viola; Dan Belov (CoRR, 2019)

A General Approach to Fairness with Optimal Transport. - Silvia Chiappa; Ray Jiang; Tom Stepleton; Aldo Pacchiano; Heinrich Jiang; John Aslanides (AAAI, 2020)

Behaviour Suite for Reinforcement Learning. - Ian Osband; Yotam Doron; Matteo Hessel; John Aslanides; Eren Sezener; Andre Saraiva 001; Katrina McKinney; Tor Lattimore; Csaba Szepesvári; Satinder Singh 001; Benjamin Van Roy; Richard S. Sutton; et al. (ICLR, 2020)

Divide-and-Conquer Monte Carlo Tree Search For Goal-Directed Planning. - Giambattista Parascandolo; Lars Buesing; Josh Merel; Leonard Hasenclever; John Aslanides; Jessica B. Hamrick; Nicolas Heess; Alexander Neitz; Theophane Weber (CoRR, 2020)

Acme: A Research Framework for Distributed Reinforcement Learning. - Matt Hoffman 001; Bobak Shahriari; John Aslanides; Gabriel Barth-Maron; Feryal M. P. Behbahani; Tamara Norman; Abbas Abdolmaleki; Albin Cassirer; Fan Yang; Kate Baumli; Sarah Henderson; Alexander Novikov 001; et al. (CoRR, 2020)

Scaling Language Models: Methods, Analysis & Insights from Training Gopher. - Jack W. Rae; Sebastian Borgeaud; Trevor Cai; Katie Millican; Jordan Hoffmann; H. Francis Song; John Aslanides; Sarah Henderson; Roman Ring; Susannah Young; Eliza Rutherford; Tom Hennigan; et al. (CoRR, 2021)

Red Teaming Language Models with Language Models. - Ethan Perez; Saffron Huang; H. Francis Song; Trevor Cai; Roman Ring; John Aslanides; Amelia Glaese; Nat McAleese; Geoffrey Irving (EMNLP, 2022)

Fine-tuning language models to find agreement among humans with diverse preferences. - Michiel A. Bakker; Martin J. Chadwick; Hannah Sheahan; Michael Henry Tessler; Lucy Campbell-Gillingham; Jan Balaguer; Nat McAleese; Amelia Glaese; John Aslanides; Matt M. Botvinick; Christopher Summerfield (NeurIPS, 2022)

Teaching language models to support answers with verified quotes. - Jacob Menick; Maja Trebacz; Vladimir Mikulik; John Aslanides; H. Francis Song; Martin J. Chadwick; Mia Glaese; Susannah Young; Lucy Campbell-Gillingham; Geoffrey Irving; Nat McAleese (CoRR, 2022)

Improving alignment of dialogue agents via targeted human judgements. - Amelia Glaese; Nat McAleese; Maja Trebacz; John Aslanides; Vlad Firoiu; Timo Ewalds; Maribeth Rauh; Laura Weidinger; Martin J. Chadwick; Phoebe Thacker; Lucy Campbell-Gillingham; Jonathan Uesato; et al. (CoRR, 2022)

Fine-Tuning Language Models via Epistemic Neural Networks. - Ian Osband; Seyed Mohammad Asghari; Benjamin Van Roy; Nat McAleese; John Aslanides; Geoffrey Irving (CoRR, 2022)