<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>This study presents a method for the dynamic value assignment of evolutionary parameters to accelerate, automate and generalise the neuroevolutionary method of ship handling for different navigational tasks and in different environmental conditions. The island model of population is used in the modified neuroevolutionary method to achieve this goal. Three different navigational situations are considered in the simulation, namely, passing through restricted waters, crossing with another vessel and overtaking in the open sea. The results of the simulation examples show that the island model performs better than a single non-divided population and may accelerate some complex and dynamic navigational tasks. This adaptive island-based neuroevolutionary system used for the COLREG manoeuvres and for the finding safe ship’s route to a given destination in restricted waters increases the accuracy and flexibility of the simulation process. The time statistics show that the time of simulation of island NEAT was shortened by 6.8% to 27.1% in comparison to modified NEAT method.</p>
</abstract>

This study presents a method for the dynamic value assignment of evolutionary parameters to accelerate, automate and generalise the neuroevolutionary method of ship handling for different navigational tasks and in different environmental conditions. The island model of population is used in the modified neuroevolutionary method to achieve this goal. Three different navigational situations are considered in the simulation, namely, passing through restricted waters, crossing with another vessel and overtaking in the open sea. The results of the simulation examples show that the island model performs better than a single non-divided population and may accelerate some complex and dynamic navigational tasks. This adaptive island-based neuroevolutionary system used for the COLREG manoeuvres and for the finding safe ship’s route to a given destination in restricted waters increases the accuracy and flexibility of the simulation process. The time statistics show that the time of simulation of island NEAT was shortened by 6.8% to 27.1% in comparison to modified NEAT method.

An Adaptive Island Model of Population for Neuroevolutionary Ship Handling

Polish Maritime Research

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

{"article-title":"An Adaptive Island Model of Population for Neuroevolutionary Ship Handling"}

This study presents a method for the dynamic value assignment of evolutionary parameters to accelerate, automate and generalise the neuroevolutionary method of...

An Adaptive Island Model of Population for Neuroevolutionary Ship Handling

Publié en ligne: 01 janv. 2022

Pages: 142 - 150

DOI: https://doi.org/10.2478/pomr-2021-0056

Mots clés
artificial neural networks, evolutionary algorithms, neuroevolution, ship movement control, ship manoeuvring

© 2021 Mathematical Institute, Slovak Academy of Sciences

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

An Adaptive Island Model of Population for Neuroevolutionary Ship Handling

Publié en ligne: 01 janv. 2022

Pages: 142 - 150

DOI: https://doi.org/10.2478/pomr-2021-0056

Mots clésartificial neural networks, evolutionary algorithms, neuroevolution, ship movement control, ship manoeuvring

© 2021 Mathematical Institute, Slovak Academy of Sciences

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Mots clés
artificial neural networks, evolutionary algorithms, neuroevolution, ship movement control, ship manoeuvring