A Hierarchical Approach to Evolving Behaviour-Trees for Swarm Control

Montague, Kirsty; Hart, Emma; Paechter, Ben

Abstract

Behaviour trees (BTs) are commonly used as controllers in robotic swarms due their modular composition and to the fact that they can be easily interpreted by humans. From an algorithmic perspective, an additional advantage is that extra modules can easily be introduced and incorporated into new trees. Genetic Programming (GP) has already been shown to be capable of evolving BTs to achieve a variety of sub-tasks (primitives) of a higher-level goal. In this work we show that a hierarchical controller can be evolved that first uses GP to evolve a repertoire of primitives expressed as BTs, and then to evolve a high-level BT controller that leverages the evolved repertoire for a foraging task. We show that the hierarchical approach that uses BTs at two levels outperforms a baseline in which the BTs are evolved using only low-level nodes. In addition, we propose a method to improve the quality of the primitive repertoire, which in turn results in improved high-level BTs.

Citation

Montague, K., Hart, E., & Paechter, B. (2024). A Hierarchical Approach to Evolving Behaviour-Trees for Swarm Control. In S. Smith, J. Correia, & C. Cintrano (Eds.), Applications of Evolutionary Computation: 27th European Conference, EvoApplications 2024, Held as Part of EvoStar 2024, Aberystwyth, UK, April 3–5, 2024, Proceedings, Part I (178-193). https://doi.org/10.1007/978-3-031-56852-7_12

• Conference Name: EvoStar 2024
• Conference Location: Aberystwyth
• Start Date: Apr 3, 2024
• End Date: Apr 5, 2024
• Acceptance Date: Jan 10, 2024
• Online Publication Date: Mar 21, 2024
• Publication Date: 2024
• Deposit Date: Feb 7, 2024
• Publicly Available Date: Mar 22, 2025
• Publisher: Springer
• Pages: 178-193
• Series Title: Lecture Notes in Computer Science (LNCS)
• Series Number: 14634
• Series ISSN: 0302-9743
• Book Title: Applications of Evolutionary Computation: 27th European Conference, EvoApplications 2024, Held as Part of EvoStar 2024, Aberystwyth, UK, April 3–5, 2024, Proceedings, Part I
• ISBN: 9783031568510
• DOI: https://doi.org/10.1007/978-3-031-56852-7_12
• Public URL: http://researchrepository.napier.ac.uk/Output/3504046