29 citations · 39 across the 5 of their papers we have counts for
7 papers
PyFlyt -- UAV Simulation Environments for Reinforcement Learning Research
Jun Jet Tai, Jim Wong, Mauro Innocente +3
Unmanned aerial vehicles (UAVs) have numerous applications, but their efficient and optimal flight can be a challenge. Reinforcement Learning (RL) has emerged as a promising approa…
Some Supervision Required: Incorporating Oracle Policies in Reinforcement Learning via Epistemic Uncertainty Metrics
Jun Jet Tai, Jordan K. Terry, Mauro S. Innocente +2
An inherent problem of reinforcement learning is performing exploration of an environment through random actions, of which a large portion can be unproductive. Instead, exploration…
Differential radial basis function network for sequence modelling
Kojo Sarfo Gyamfi, James Brusey, Elena Gaura
We propose a differential radial basis function (RBF) network termed RBF-DiffNet -- whose hidden layer blocks are partial differential equations (PDEs) linear in terms of the RBF -…
Proof of Concept of Wireless TERS Monitoring
Michael Allen, Elena Gaura, Ross Wilkins +3
Temporary earth retaining structures (TERS) help prevent collapse during construction excavation. To ensure that these structures are operating within design specifications, load f…
Reinforcement Learning-based Thermal Comfort Control for Vehicle Cabins
James Brusey, Diana Hintea, Elena Gaura +1
Vehicle climate control systems aim to keep passengers thermally comfortable. However, current systems control temperature rather than thermal comfort and tend to be energy hungry,…
K-Means Clustering using Tabu Search with Quantized Means
Kojo Sarfo Gyamfi, James Brusey, Andrew Hunt
The Tabu Search (TS) metaheuristic has been proposed for K-Means clustering as an alternative to Lloyd's algorithm, which for all its ease of implementation and fast runtime, has t…
Linear classifier design under heteroscedasticity in Linear Discriminant Analysis
Kojo Sarfo Gyamfi, James Brusey, Andrew Hunt +1
Under normality and homoscedasticity assumptions, Linear Discriminant Analysis (LDA) is known to be optimal in terms of minimising the Bayes error for binary classification. In the…