Behavior Allocations in Robotic Collective Herding Behavior Evolution

Valjee, Ameel and Aslan, Bilal and Nitschke, Geoff (2025) Behavior Allocations in Robotic Collective Herding Behavior Evolution, Proceedings of IEEE Congress on Evolutionary Computation (IEEE CEC 2025), Hangzhou, China, IEEE Press.

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Abstract

Behavioral heterogeneity yields problem solving benefits in biological collective behavior systems such as insect colonies and human societies and in artificial collective behavior systems such as distributed computer networks and swarmrobotics systems. In this study, we investigate comparative methods for two-step collective behavior evolution designed to encourage the evolution of behavioral diversity in swarm robotic applications. Specifically, we investigate behavioral diversity evolution given pre-evolved behaviors in collective behaviors that are effective across increasingly complex and difficult collective herding task environments. Results indicate that a minimal complement of pre-evolved (lower task-performance) collective herding behaviors was suitable for achieving high task performance across all environments and task difficulty levels. Results support the efficacy of the two-step approach for evolving behaviorally heterogeneous groups in collective behavior tasks that benefit.

Item Type:	Conference paper
Subjects:	Computing methodologies > Artificial intelligence
Date Deposited:	13 Oct 2025 12:27
Last Modified:	13 Oct 2025 12:27
URI:	https://pubs.cs.uct.ac.za/id/eprint/1747

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