A Novel Space Filling Curves Based Approach to PSO Algorithms for Autonomous Agents

Logofătu, Doina; Sobol, Gil; Stamate, Daniel and Balabanov, Kristiyan. 2017. 'A Novel Space Filling Curves Based Approach to PSO Algorithms for Autonomous Agents'. In: ICCCI 2017: 9th International Conference on Computational Collective Intelligence. Nicosia, Cyprus. [Conference or Workshop Item]

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Abstract or Description

In this work the swarm behavior principles of Craig W. Reynolds are combined with deterministic traits. This is done by using leaders with motions based on space filling curves like Peano and Hilbert. Our goal is to evaluate how the swarm of agents works with this approach, supposing the entire swarm will better explore the entire space. Therefore, we examine different combinations of Peano and Hilbert with the already known swarm algorithms and test them in a practical challenge for the harvesting of manganese nodules on the sea ground with the use of autonomous robots. We run experiments with various settings, then evaluate and describe the results. In the last section some further development ideas and thoughts for the expansion of this study are considered.

Item Type:

Conference or Workshop Item (Paper)

Identification Number (DOI):



Autonomous agents, Space filling curves, Particle swarm optimization, Deterministic leaders, Application

Departments, Centres and Research Units:



7 September 2017Published Online
1 June 2017Accepted

Event Location:

Nicosia, Cyprus

Item ID:


Date Deposited:

05 Dec 2017 17:13

Last Modified:

29 Apr 2020 16:42



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