On the Cost of Evolving Task Specialization in Multi-Robot Systems

2026-03-10

AI Summary

This study addresses whether task specialization enhances efficiency in multi-robot systems under limited optimization budgets. For the first time, the authors employ evolutionary algorithms to optimize artificial neural network controllers within a constrained evaluation budget, comparing generalist strategies against task-specialized ones in a collective foraging task. The results demonstrate that task specialization, by impairing coordination among robots, leads to inferior overall performance compared to generalist behaviors. These findings challenge the conventional assumption that specialization inherently improves efficiency and offer a novel cost–benefit perspective on optimizing cooperative multi-robot systems.

Technology Category

• Intelligent Robots: Multi-Robot Systems
• Search and Optimization: Evolutionary Computation
• Multiagent Systems: Coordination and Collaboration

Application Category

• Economics, Online Markets and Human Computation: Incentives in network design for Web infrastructures and ecosystems
• Responsible Web: Human-perceived consequences of algorithmic deployment on the web
• Web Mining and Content Analysis: Robustness and generalizability of Web mining methods

Abstract

Task specialization can lead to simpler robot behaviors and higher efficiency in multi-robot systems. Previous works have shown the emergence of task specialization during evolutionary optimization, focusing on feasibility rather than costs. In this study, we take first steps toward a cost-benefit analysis of task specialization in robot swarms using a foraging scenario. We evolve artificial neural networks as generalist behaviors for the entire task and as task-specialist behaviors for subtasks within a limited evaluation budget. We show that generalist behaviors can be successfully optimized while the evolved task-specialist controllers fail to cooperate efficiently, resulting in worse performance than the generalists. Consequently, task specialization does not necessarily improve efficiency when optimization budget is limited.

Problem

• task specialization
• multi-robot systems
• evolutionary optimization
• optimization budget
• foraging

Innovation

• task specialization
• evolutionary robotics
• multi-robot systems
• cost-benefit analysis
• foraging