6 citations · 10 across the 5 of their papers we have counts for
5 papers
A Future Capabilities Agent for Tactical Air Traffic Control
Paul Kent, George De Ath, Martin Layton +3
Escalating air traffic demand is driving the adoption of automation to support air traffic controllers, but existing approaches face a trade-off between safety assurance and interp…
Machine learning-based prediction of Q-voter model in complex networks
Aruane M. Pineda, Paul Kent, Colm Connaughton +1
In this article, we consider machine learning algorithms to accurately predict two variables associated with the -voter model in complex networks, i.e., (i) the consensus time a…
BOP-Elites, a Bayesian Optimisation Approach to Quality Diversity Search with Black-Box descriptor functions
Paul Kent, Adam Gaier, Jean-Baptiste Mouret +1
Quality Diversity (QD) algorithms such as MAP-Elites are a class of optimisation techniques that attempt to find many high performing points that all behave differently according t…
Tackling Neural Architecture Search With Quality Diversity Optimization
Lennart Schneider, Florian Pfisterer, Paul Kent +3
Neural architecture search (NAS) has been studied extensively and has grown to become a research field with substantial impact. While classical single-objective NAS searches for th…
BOP-Elites, a Bayesian Optimisation algorithm for Quality-Diversity search
Paul Kent, Juergen Branke
Quality Diversity (QD) algorithms such as MAP-Elites are a class of optimisation techniques that attempt to find a set of high-performing points from an objective function while en…