PSO-based search rules for aerial swarms against unexplored vector fields via genetic programming

Palina Bartashevich, Illya Bakurov, Sanaz Mostaghim, Leonardo Vanneschi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

In this paper, we study Particle Swarm Optimization (PSO) as a collective search mechanism for individuals (such as aerial micro-robots) which are supposed to search in environments with unknown external dynamics. In order to deal with the unknown disturbance, we present new PSO equations which are evolved using Genetic Programming (GP) with a semantically diverse starting population, seeded by the Evolutionary Demes Despeciation Algorithm (EDDA), that generalizes better than standard GP in the presence of unknown dynamics. The analysis of the evolved equations shows that with only small modifications in the velocity equation, PSO can achieve collective search behavior while being unaware of the dynamic external environment, mimicking the zigzag upwind flights of birds towards the food source.

Original languageEnglish
Title of host publicationParallel Problem Solving from Nature – PPSN XV
Subtitle of host publication15th International Conference, 2018, Proceedings
PublisherSpringer Verlag
Pages41-53
Number of pages13
ISBN (Print)9783319992525
DOIs
Publication statusPublished - 1 Jan 2018
Event15th International Conference on Parallel Problem Solving from Nature, PPSN 2018 - Coimbra, Portugal
Duration: 8 Sep 201812 Sep 2018

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11101 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference15th International Conference on Parallel Problem Solving from Nature, PPSN 2018
CountryPortugal
CityCoimbra
Period8/09/1812/09/18

Keywords

  • EDDA
  • Genetic Programming
  • Particle swarm optimization
  • Semantics
  • Vector fields

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  • Cite this

    Bartashevich, P., Bakurov, I., Mostaghim, S., & Vanneschi, L. (2018). PSO-based search rules for aerial swarms against unexplored vector fields via genetic programming. In Parallel Problem Solving from Nature – PPSN XV: 15th International Conference, 2018, Proceedings (pp. 41-53). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11101 LNCS). Springer Verlag. https://doi.org/10.1007/978-3-319-99253-2_4