17 citations · 17 across the 5 of their papers we have counts for
4 papers · 1 filter
Task Adaptation of Reinforcement Learning-based NAS Agents through Transfer Learning
Amber Cassimon, Siegfried Mercelis, Kevin Mets
Recently, a novel paradigm has been proposed for reinforcement learning-based NAS agents, that revolves around the incremental improvement of a given architecture. We assess the ab…
Designing a Classifier for Active Fire Detection from Multispectral Satellite Imagery Using Neural Architecture Search
Amber Cassimon, Phil Reiter, Siegfried Mercelis +1
This paper showcases the use of a reinforcement learning-based Neural Architecture Search (NAS) agent to design a small neural network to perform active fire detection on multispec…
Scalable Reinforcement Learning-based Neural Architecture Search
Amber Cassimon, Siegfried Mercelis, Kevin Mets
In this publication, we assess the ability of a novel Reinforcement Learning-based solution to the problem of Neural Architecture Search, where a Reinforcement Learning (RL) agent…
A Review of the Deep Sea Treasure problem as a Multi-Objective Reinforcement Learning Benchmark
Amber Cassimon, Reinout Eyckerman, Siegfried Mercelis +2
In this paper, the authors investigate the Deep Sea Treasure (DST) problem as proposed by Vamplew et al. Through a number of proofs, the authors show the original DST problem to be…