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| Main Authors: | , , , |
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| Format: | Preprint |
| Published: |
2026
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2603.09552 |
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| _version_ | 1866917329507450880 |
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| author | Leopardi, Paolo Hamann, Heiko Kuckling, Jonas Kaiser, Tanja Katharina |
| author_facet | Leopardi, Paolo Hamann, Heiko Kuckling, Jonas Kaiser, Tanja Katharina |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2603_09552 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | On the Cost of Evolving Task Specialization in Multi-Robot Systems Leopardi, Paolo Hamann, Heiko Kuckling, Jonas Kaiser, Tanja Katharina Robotics 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. |
| title | On the Cost of Evolving Task Specialization in Multi-Robot Systems |
| topic | Robotics |
| url | https://arxiv.org/abs/2603.09552 |