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Evolution of a Functionally Diverse Swarm via a Novel Decentralised Quality-Diversity Algorithm

Conference Proceeding
Hart, E., Steyven, A. S. W., & Paechter, B. (2018)
Evolution of a Functionally Diverse Swarm via a Novel Decentralised Quality-Diversity Algorithm. In GECCO '18 Proceedings of the Genetic and Evolutionary Computation Conference, (101-108). https://doi.org/10.1145/3205455.3205481
The presence of functionality diversity within a group has been demonstrated to lead to greater robustness, higher performance and increased problem-solving ability in a broad...

Clustering Moving Data with a Modified Immune Algorithm

Conference Proceeding
Hart, E., & Ross, P. (2001)
Clustering Moving Data with a Modified Immune Algorithm. In E. Boers (Ed.), Applications of Evolutionary Computing, 394-403. https://doi.org/10.1007/3-540-45365-2_41
In this paper we present a prototype of a new model for performing clustering in large, non-static databases. Although many machine learning algorithms for data clustering hav...

Algorithm selection using deep learning without feature extraction

Conference Proceeding
Alissa, M., Sim, K., & Hart, E. (2019)
Algorithm selection using deep learning without feature extraction. In GECCO '19: Proceedings of the Genetic and Evolutionary Computation Conference Companion. , (198-206). https://doi.org/10.1145/3321707.3321845
We propose a novel technique for algorithm-selection which adopts a deep-learning approach, specifically a Recurrent-Neural Network with Long-Short-Term-Memory (RNN-LSTM). In ...

On Constructing Ensembles for Combinatorial Optimisation

Journal Article
Hart, E., & Sim, K. (2018)
On Constructing Ensembles for Combinatorial Optimisation. Evolutionary Computation, 26(1), 67-87. https://doi.org/10.1162/evco_a_00203
Although the use of ensemble methods in machine-learning is ubiquitous due to their proven ability to outperform their constituent algorithms, ensembles of optimisation algori...