On Dynamical Genetic Programming: Random Boolean Networks in Learning Classifier Systems. - Larry Bull; Richard Preen (EuroGP, 2009)

An XCS approach to forecasting financial time series. - Richard Preen (GECCO (Companion), 2009)

Discrete dynamical genetic programming in XCS. - Richard Preen; Larry Bull (GECCO, 2009)

Identifying Trade Entry and Exit Timing Using Mathematical Technical Indicators in XCS. - Richard Preen (IWLCS, 2009)

Arithmetic dynamical genetic programming in the XCSF Learning Classifier System. - Richard Preen; Larry Bull (IEEE Congress on Evolutionary Computation, 2011)

Fuzzy dynamical genetic programming in XCSF. - Richard Preen; Larry Bull (GECCO (Companion), 2011)

Dynamical genetic programming in learning classifier systems. - Richard John Preen (2011)

Evolution of Supershapes for the Generation of Three-Dimensional Designs - Richard Preen; Larry Bull (CoRR, 2012)

Towards the evolution of novel vertical-axis wind turbines. - Richard Preen; Larry Bull (UKCI, 2013)

Towards the Coevolution of Novel Vertical-Axis Wind Turbines. - Richard Preen; Larry Bull (CoRR, 2013)

Dynamical Genetic Programming in XCSF. - Richard Preen; Larry Bull (Evol. Comput., 2013)

Design Mining Interacting Wind Turbines: Surrogate-Assisted Coevolution of Rapid Prototyped VAWT. - Richard John Preen; Larry Bull (CoRR, 2014)

Towards the evolution of vertical-axis wind turbines using supershapes. - Richard John Preen; Larry Bull (Evol. Intell., 2014)

Discrete and fuzzy dynamical genetic programming in the XCSF learning classifier system. - Richard Preen; Larry Bull (Soft Comput., 2014)

Design Mining VAWT Wind Farms. - Richard John Preen; Larry Bull (CoRR, 2015)

Toward the Coevolution of Novel Vertical-Axis Wind Turbines. - Richard John Preen; Larry Bull (IEEE Trans. Evol. Comput., 2015)

Design Mining Interacting Wind Turbines. - Richard John Preen; Larry Bull (Evol. Comput., 2016)

On Design Mining: Coevolution and Surrogate Models. - Richard John Preen; Larry Bull (Artif. Life, 2017)

Towards an evolvable cancer treatment simulator. - Richard John Preen; Larry Bull; Andrew Adamatzky (Biosyst., 2019)

Autoencoding with XCSF. - Richard John Preen; Stewart W. Wilson; Larry Bull (CoRR, 2019)

Design mining microbial fuel cell cascades. - Richard John Preen; Jiseon You; Larry Bull; Ioannis A. Ieropoulos (Soft Comput., 2019)

Evolutionary n-Level Hypergraph Partitioning With Adaptive Coarsening. - Richard John Preen; Jim E. Smith (IEEE Trans. Evol. Comput., 2019)

Deep Learning with a Classifier System: Initial Results. - Richard John Preen; Larry Bull (CoRR, 2021)

Autoencoding With a Classifier System. - Richard John Preen; Stewart W. Wilson; Larry Bull (IEEE Trans. Evol. Comput., 2021)

GRAIMATTER Green Paper: Recommendations for disclosure control of trained Machine Learning (ML) models from Trusted Research Environments (TREs). - Emily R. Jefferson; James Liley; Maeve Malone; Smarti Reel; Alba Crespi-Boixader; Xaroula Kerasidou; Francesco Tava; Andrew McCarthy; Richard Preen; Alberto Blanco-Justicia; Esma Mansouri-Benssassi; Josep Domingo-Ferrer; et al. (CoRR, 2022)

Safe machine learning model release from Trusted Research Environments: The AI-SDC package. - Jim Smith 002; Richard John Preen; Andrew McCarthy; Alba Crespi-Boixader; James Liley; Simon Rogers (CoRR, 2022)

ACRO: A multi-language toolkit for supporting Automated Checking of Research Outputs. - Richard John Preen; Jim Smith 002 (CoRR, 2022)

A hierarchical approach for assessing the vulnerability of tree-based classification models to membership inference attack. - Richard John Preen; Jim E. Smith (CoRR, 2025)