Conference Proceeding

Neuroevolution Trajectory Networks of the Behaviour Space



Sarti S, Adair J & Ochoa G (2022) Neuroevolution Trajectory Networks of the Behaviour Space. In: Jiménez Laredo JL, Hidalgo JI & Babaagba KO (eds.) Applications of Evolutionary Computation. Lecture Notes in Computer Science, 13224. EvoApplications 2022, Madrid, Spain, 20.04.2022-22.04.2022. Cham, Switzerland: Springer International Publishing, pp. 685-703.

A network-based modelling technique, search trajectory networks (STNs), has recently helped to understand the dynamics of neuroevolution algorithms such as NEAT. Modelling and visualising variants of NEAT made it possible to analyse the dynamics of search operators. Thus far, this analysis was applied directly to the NEAT genotype space composed of neural network topologies and weights. Here, we extend this work, by illuminating instead the behavioural space, which is available when the evolved neural networks control the behaviour of agents. Recent interest in behaviour characterisation highlights the need for divergent search strategies. Quality-diversity and Novelty search are examples of divergent search, but their dynamics are not yet well understood. In this article, we examine the idiosyncrasies of three neuroevolution variants: novelty, random and objective search operating as usual on the genotypic search space, but analysed in the behavioural space. Results show that novelty is a successful divergent search strategy. However, its abilities to produce diverse solutions are not always consistent. Our visual analysis highlights interesting relationships between topological complexity and behavioural diversity which may pave the way for new characterisations and search strategies.

Search trajectory networks; Behavioural space; NEAT; Novelty search; Divergent search

Title of seriesLecture Notes in Computer Science
Number in series13224
Publication date31/12/2022
Publication date online30/04/2022
PublisherSpringer International Publishing
Place of publicationCham, Switzerland
ISSN of series0302-9743
ConferenceEvoApplications 2022
Conference locationMadrid, Spain

People (3)


Dr Jason Adair
Dr Jason Adair

Lecturer in Data Science, Computing Science

Professor Gabriela Ochoa
Professor Gabriela Ochoa

Professor, Computing Science

Mr Stefano Sarti
Mr Stefano Sarti

Tutor (ASF), Computing Science