@inproceedings{293c2540a5a64fb19eb72f611352e615,
title = "Rapid Phenotypic Landscape Exploration Through Hierarchical Spatial Partitioning",
abstract = "Exploration of the search space through the optimisation of phenotypic diversity is of increasing interest within the field of evolutionary robotics. Novelty search and the more recent MAP-Elites are two state of the art evolutionary algorithms which diversify low dimensional phenotypic traits for divergent exploration. In this paper we introduce a novel alternative for rapid divergent search of the feature space. Unlike previous phenotypic search procedures, our proposed Spatial, Hierarchical, Illuminated Neuro-Evolution (SHINE) algorithm utilises a tree structure for the maintenance and selection of potential candidates. SHINE penalises previous solutions in more crowded areas of the landscape. Our experimental results show that SHINE significantly outperforms novelty search and MAP-Elites in both performance and exploration. We conclude that the SHINE algorithm is a viable method for rapid divergent search of low dimensional, phenotypic landscapes.",
keywords = "Algorithm Analysis and Problem Complexity, Algorithm design, Artificial Intelligence (incl. Robotics), Computational Biology/Bioinformatics, Computation by Abstract Devices, Discrete Mathematics in Computer Science, evolutionary robotics, neuroevolution, Pattern Recognition, Phenotypic diversity",
author = "Davy Smith and Laurissa Tokarchuk and Geraint Wiggins",
year = "2016",
month = sep,
doi = "10.1007/978-3-319-45823-6_85",
language = "English",
isbn = "978-3-319-45822-9 978-3-319-45823-6",
series = "Lecture Notes in Computer Science",
publisher = "Springer",
pages = "911--920",
editor = "Julia Handl and Emma Hart and Lewis, {Peter R.} and Manuel L{\'o}pez-Ib{\'a}{\~n}ez and Gabriela Ochoa and Ben Paechter",
booktitle = "Parallel Problem Solving from Nature -- PPSN XIV",
address = "Germany",
}