A ZoomTree interface for searching genealogical information. - Janet Wesson; Mathys C. du Plessis; Craig Oosthuizen (Afrigraph, 2004)

Improved differential evolution for dynamic optimization problems. - Mathys C. du Plessis; Andries P. Engelbrecht (IEEE Congress on Evolutionary Computation, 2008)

Incorporating layout managers into an evolutionary programming algorithm to design graphical user interfaces. - Mathys C. du Plessis; Lynette Barnard (SAICSIT, 2008)

Models towards a hybrid conversational agent for contact centres. - Gopal Ravi Sankar; Jéan H. Greyling; Dieter Vogts; Mathys C. du Plessis (SAICSIT, 2008)

A hybrid neural network and Minimax algorithm for zero-sum games. - Mathys C. du Plessis (SAICSIT, 2009)

Towards an artificial neural network-based simulator for behavioural evolution in evolutionary robotics. - Christiaan J. Pretorius; Mathys C. du Plessis; Charmain Cilliers (SAICSIT, 2009)

Incorporating structured text retrieval into the extended Boolean model. - Mathys C. du Plessis; Gideon de V. de Kock (Comput. Informatics, 2009)

A Neural Network-based kinematic and light-perception simulator for simple robotic evolution. - Christiaan J. Pretorius; Mathys C. du Plessis; Charmain Cilliers (IEEE Congress on Evolutionary Computation, 2010)

Toward database inference by GUI analysis: a case study. - Meredith A. Barnes; Mathys C. du Plessis; Brenda Scholtz (SAICSIT, 2010)

Does Chomsky complexity affect genetic programming computational requirements? - Clayton Burger; Mathys C. du Plessis (SAICSIT, 2011)

Self-adaptive competitive differential evolution for dynamic environments. - Mathys C. du Plessis; Andries P. Engelbrecht (SDE, 2011)

Using Competitive Population Evaluation in a differential evolution algorithm for dynamic environments. - Mathys C. du Plessis; Andries P. Engelbrecht (Eur. J. Oper. Res., 2012)

Design and parametric considerations for artificial neural network pruning in UCT game playing. - Clayton Burger; Mathys C. du Plessis; Charmain Cilliers (SAICSIT, 2013)

Differential evolution for dynamic environments with unknown numbers of optima. - Mathys C. du Plessis; Andries P. Engelbrecht (J. Glob. Optim., 2013)

Simulating Robots Without Conventional Physics: A Neural Network Approach. - Christiaan J. Pretorius; Mathys C. du Plessis; Charmain Cilliers (J. Intell. Robotic Syst., 2013)

Self-Adaptive Differential Evolution for Dynamic Environments with Fluctuating Numbers of Optima. - Mathys C. du Plessis; Andries P. Engelbrecht (Metaheuristics for Dynamic Optimization, 2013)

A comparison of neural networks and physics models as motion simulators for simple robotic evolution. - Christiaan J. Pretorius; Mathys C. du Plessis; John W. Gonsalves (IEEE Congress on Evolutionary Computation, 2014)

Self-Adapting the Brownian Radius in a Differential Evolution Algorithm for Dynamic Environments. - Mathys C. du Plessis; Andries P. Engelbrecht; André P. Calitz (FOGA, 2015)

Using Standard Components in Evolutionary Robotics to Produce an Inexpensive Robot Arm. - Michael W. Louwrens; Mathys C. du Plessis; Jéan H. Greyling (NaBIC, 2015)

Evolving Snake Robot Controllers Using Artificial Neural Networks as an Alternative to a Physics-Based Simulator. - Grant W. Woodford; Mathys C. du Plessis; Christiaan J. Pretorius (SSCI, 2015)

Hybridising Ant Colony Optimisation with a upper confidence bound algorithm for routing and wavelength assignment in an optical burst switching network. - Andrew S. Gravett; Mathys C. du Plessis; Timothy B. Gibbon (SSCI, 2016)

Concurrent controller and Simulator Neural Network development for a differentially-steered robot in Evolutionary Robotics. - Grant W. Woodford; Christiaan J. Pretorius; Mathys C. du Plessis (Robotics Auton. Syst., 2016)

Implementation and validation of an Omnet++ optical burst switching simulator. - Joshua Oladipo; Mathys C. du Plessis; Timothy B. Gibbon (PEMWN, 2017)

The transferability of evolved hexapod locomotion controllers from simulation to real hardware. - Christiaan J. Pretorius; Mathys C. du Plessis; John W. Gonsalves (RCAR, 2017)

Neuroevolution of Inverted Pendulum Control: A Comparative Study of Simulation Techniques. - Christiaan J. Pretorius; Mathys C. du Plessis; John W. Gonsalves (J. Intell. Robotic Syst., 2017)

A distributed ant-based algorithm for routing and wavelength assignment in an optical burst switching flexible spectrum network with transmission impairments. - Andrew S. Gravett; Mathys C. du Plessis; Timothy B. Gibbon (Photonic Netw. Commun., 2017)

Concurrent controller and Simulator Neural Network development for a snake-like robot in Evolutionary Robotics. - Grant W. Woodford; Mathys C. du Plessis; Christiaan J. Pretorius (Robotics Auton. Syst., 2017)

Robotic snake simulation using ensembles of artificial neural networks in evolutionary robotics. - Grant W. Woodford; Mathys C. du Plessis (GECCO, 2018)

Dropout algorithms for recurrent neural networks. - Nathan Watt; Mathys C. du Plessis (SAICSIT, 2018)

Dropout for Recurrent Neural Networks. - Nathan Watt; Mathys C. du Plessis (INNSBDDL, 2019)

Towards the Incorporation of Proprioception in Evolutionary Robotics Controllers. - Antin Phillips; Mathys C. du Plessis (IRC, 2019)

Ant Colony Optimization on an OBS Network with Link Cost and Impairments. - François Du Plessis; Mathys C. du Plessis; Tim Gibbon (ISDA, 2019)

Evolutionary Robotics Applied to Hexapod Locomotion: a Comparative Study of Simulation Techniques. - Christiaan J. Pretorius; Mathys C. du Plessis; John W. Gonsalves (J. Intell. Robotic Syst., 2019)

Evolutionary Robotics Controllers with Proprioception Facilitated by Neural-Network-Based Simulators. - Antin Phillips; Mathys C. du Plessis (Artif. Life, 2020)

Bootstrapped Neuro-Simulation as a method of concurrent neuro-evolution and damage recovery. - Brydon A. Leonard; Mathys C. du Plessis; Grant W. Woodford (Robotics Auton. Syst., 2020)

Complex Morphology Neural Network Simulation in Evolutionary Robotics. - Grant W. Woodford; Mathys C. du Plessis (Robotica, 2020)

Adaptive Navigation Strategies in Evolutionary Robotics Controllers with Location Perception. - Antin Phillips; Mathys C. du Plessis (CEC, 2021)

Avoiding Unexpected Obstacles During Robotic Navigation Using Rapidly-Exploring Random Trees and a Neural Network Simulator. - Bouwer Botha; Mathys C. du Plessis (SACAIR, 2021)

Revisiting the Use of Noise in Evolutionary Robotics. - Mathys C. du Plessis; Antin P. Phillips; Christiaan J. Pretorius (SACAIR, 2021)

Bootstrapped Neuro-Simulation for complex robots. - Grant W. Woodford; Mathys C. du Plessis (Robotics Auton. Syst., 2021)

Bootstrapped Neuro-Simulation for Damage Recovery in Complex Robots. - Brydon A. Leonard; Mathys C. du Plessis (CEC, 2022)

Towards robot vision using deep neural networks in evolutionary robotics. - Nathan Watt; Mathys C. du Plessis (Evol. Intell., 2022)

Congestion aware ant colony optimisation algorithm for routing and spectrum assignment in flexi-grid optical burst switching networks. - Joshua Oladipo; Mathys C. du Plessis; Timothy B. Gibbon (Photonic Netw. Commun., 2023)

Neuro-augmented vision for evolutionary robotics. - Nathan Watt; Mathys C. du Plessis (Mach. Vis. Appl., 2023)