4 papers
Risk-Aware Reinforcement Learning for Mobile Manipulation
Michael Groom, James Wilson, Nick Hawes +1
For robots to successfully transition from lab settings to everyday environments, they must begin to reason about the risks associated with their actions and make informed, risk-aw…
Distillation and Interpretability of Ensemble Forecasts of ENSO Phase using Entropic Learning
Michael Groom, Davide Bassetti, Illia Horenko +1
This paper introduces a distillation framework for an ensemble of entropy-optimal Sparse Probabilistic Approximation (eSPA) models, trained exclusively on satellite-era observation…
An entropy-optimal path to humble AI
Davide Bassetti, Lukáš Pospíšil, Michael Groom +2
Progress of AI has led to very successful, but by no means humble models and tools, especially regarding (i) the huge and further exploding costs and resources they demand, and (ii…
Entropic learning enables skilful forecasts of ENSO phase at up to two years lead time
Michael Groom, Davide Bassetti, Illia Horenko +1
This paper extends previous work (Groom et al., \emph{Artif. Intell. Earth Syst.}, 2024) in applying the entropy-optimal Sparse Probabilistic Approximation (eSPA) algorithm to pred…