Search Results for author: Richard J. Preen

Found 11 papers, 1 papers with code

Deep Learning with a Classifier System: Initial Results

no code implementations1 Mar 2021 Richard J. Preen, Larry Bull

This article presents the first results from using a learning classifier system capable of performing adaptive computation with deep neural networks.

Handwritten Digit Recognition

Autoencoding with a Classifier System

no code implementations23 Oct 2019 Richard J. Preen, Stewart W. Wilson, Larry Bull

Learning classifier systems (LCS) are a framework for adaptively subdividing input spaces into an ensemble of simpler local approximations that together cover the domain.

Dimensionality Reduction

Towards an Evolvable Cancer Treatment Simulator

no code implementations19 Dec 2018 Richard J. Preen, Larry Bull, Andrew Adamatzky

The use of high-fidelity computational simulations promises to enable high-throughput hypothesis testing and optimisation of cancer therapies.

Two-sample testing

Evolutionary n-level Hypergraph Partitioning with Adaptive Coarsening

no code implementations25 Mar 2018 Richard J. Preen, Jim Smith

This article presents a novel memetic algorithm which remains effective on larger initial hypergraphs.

hypergraph partitioning

Design Mining Microbial Fuel Cell Cascades

no code implementations18 Oct 2016 Richard J. Preen, Jiseon You, Larry Bull, Ioannis A. Ieropoulos

Microbial fuel cells (MFCs) perform wastewater treatment and electricity production through the conversion of organic matter using microorganisms.

On Design Mining: Coevolution and Surrogate Models

no code implementations29 Jun 2015 Richard J. Preen, Larry Bull

Design mining is the use of computational intelligence techniques to iteratively search and model the attribute space of physical objects evaluated directly through rapid prototyping to meet given objectives.

Design Mining Interacting Wind Turbines

no code implementations2 Oct 2014 Richard J. Preen, Larry Bull

The accuracy of various modelling algorithms used to estimate the fitness of evaluated individuals from the initial experiments is compared.

Toward the Coevolution of Novel Vertical-Axis Wind Turbines

no code implementations13 Aug 2013 Richard J. Preen, Larry Bull

The production of renewable and sustainable energy is one of the most important challenges currently facing mankind.

Towards the Evolution of Vertical-Axis Wind Turbines using Supershapes

1 code implementation18 Apr 2012 Richard J. Preen, Larry Bull

We have recently presented an initial study of evolutionary algorithms used to design vertical-axis wind turbines (VAWTs) wherein candidate prototypes are evaluated under approximated wind tunnel conditions after being physically instantiated by a 3D printer.

3D Shape Representation

Discrete Dynamical Genetic Programming in XCS

no code implementations18 Apr 2012 Richard J. Preen, Larry Bull

A number of representation schemes have been presented for use within Learning Classifier Systems, ranging from binary encodings to neural networks.

Discrete and fuzzy dynamical genetic programming in the XCSF learning classifier system

no code implementations26 Jan 2012 Richard J. Preen, Larry Bull

A number of representation schemes have been presented for use within learning classifier systems, ranging from binary encodings to neural networks.

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