Optimization of swarm behavior assisted by an automatic local proof for a pattern formation task

Mario Coppola*, Guido C.H.E. de Croon

*Corresponding author for this work

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

3 Citations (Scopus)
84 Downloads (Pure)


In this work, we optimize the behavior of swarm agents in a pattern formation task. We start with a local behavior, expressed as a local state-action map, that has been formally proven to lead the swarm to always eventually form the desired pattern. We seek to optimize this for performance while keeping the formal proof. First, the state-action map is pruned to remove unnecessary state-action pairs, reducing the solution space. Then, the probabilities of executing the remaining actions are tuned with a genetic algorithm. The final controllers allow the swarm to form the patterns up to orders of magnitude faster than with the original behavior. The optimization is found to suffer from scalability issues. These may be tackled in future work by automatically minimizing the size of the local state-action map with a further direct focus on performance.

Original languageEnglish
Title of host publicationSwarm Intelligence - 11th International Conference, ANTS 2018, Proceedings
EditorsMarco Dorigo, Mauro Birattari, Christian Blum, Anders L. Christensen, Andreagiovanni Reina, Vito Trianni
Number of pages12
Volume11172 LNCS
ISBN (Electronic)978-3-030-00533-7
ISBN (Print)978-3-030-00532-0
Publication statusPublished - 1 Jan 2018
EventANTS 2018: 11th International Conference on Swarm Intelligence - Rome, Italy
Duration: 29 Oct 201831 Oct 2018
Conference number: 11

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11172 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


ConferenceANTS 2018: 11th International Conference on Swarm Intelligence
Abbreviated titleANTS 2018


Dive into the research topics of 'Optimization of swarm behavior assisted by an automatic local proof for a pattern formation task'. Together they form a unique fingerprint.

Cite this