18 citations · 80 across the 23 of their papers we have counts for
3 papers · 1 filter
Optimistic Exploration for Risk-Averse Constrained Reinforcement Learning
James McCarthy, Radu Marinescu, Elizabeth Daly +1
Risk-averse Constrained Reinforcement Learning (RaCRL) aims to learn policies that minimise the likelihood of rare and catastrophic constraint violations caused by an environment's…
Boolean Decision Rules for Reinforcement Learning Policy Summarisation
James McCarthy, Rahul Nair, Elizabeth Daly +2
Explainability of Reinforcement Learning (RL) policies remains a challenging research problem, particularly when considering RL in a safety context. Understanding the decisions and…
Designing Machine Learning Pipeline Toolkit for AutoML Surrogate Modeling Optimization
Paulito P. Palmes, Akihiro Kishimoto, Radu Marinescu +2
The pipeline optimization problem in machine learning requires simultaneous optimization of pipeline structures and parameter adaptation of their elements. Having an elegant way to…