The Evaluation Cost of Task Specialization in Evolutionary Multi-Robot Systems

2026-06-23

AI Summary

This study addresses the trade-off between task specialization and general-purpose strategies in evolutionary multi-robot systems, where the evaluation cost of specialized behaviors relative to generic ones remains unclear. Using a physics-based simulation platform combined with evolutionary algorithms, the authors systematically compare the performance and evaluation budget requirements of specialized versus generalist controllers across varying swarm sizes in a foraging task. The results demonstrate that, as the number of robots increases, specialized strategies consistently outperform generalist approaches while requiring significantly lower total evaluation budgets. This finding challenges the conventional assumption that specialization inherently incurs higher computational costs and provides new empirical support for leveraging task specialization in the efficient evolutionary design of large-scale multi-robot systems.

Abstract

Task specialization can improve the efficiency of multi-robot systems (MRSs). Previous works have investigated the emergence of task-specialist robot controllers through evolutionary optimization and have argued that task specialization is more likely to evolve when subtask behaviors are readily available as building blocks. However, the available evaluation budget must be distributed across all subtasks, whereas a single generalist behavior can exploit the entire budget for its own optimization. We present a cost-benefit analysis of evolving task-specialist versus generalist behaviors in a foraging scenario here. In a physics-based robotics simulator, we study the total evaluation budget required to evolve task-specialist behaviors that outperform generalist behaviors across MRS sizes. We show that with increasing MRS size, a lower total evaluation budget is sufficient to evolve specialists that outperform generalists.

Problem

• task specialization
• evaluation cost
• evolutionary multi-robot systems
• generalist behaviors
• foraging scenario

Innovation

• task specialization
• evolutionary robotics
• evaluation cost
• multi-robot systems
• generalist vs specialist