From Control Substitution to Structural Dominance: Morphological Convergence and Infrastructure Power in Autonomous Systems
Morphological Convergence and Infrastructure Power in Autonomous Systems
- Wu, Shaoyuan
Global AI Governance and Policy Research Center, EPINOVA LLC
https://orcid.org/0009-0008-0660-8232
Description
This working paper develops a structural theory of autonomous power. It argues that autonomous-system competition is moving beyond platform morphology toward orchestration architectures and infrastructure control, as engineering constraints cause drones, robotic vehicles, unmanned maritime platforms, and other autonomous systems to converge around stable morphological attractors.
Abstract
The rapid expansion of autonomous systems has intensified competition over drones, robotic vehicles, unmanned maritime platforms, and other machine agents. Yet platform-centered competition may represent only a transitional phase. As engineering constraints, operational requirements, and mission profiles converge, autonomous platforms are likely to cluster around a limited number of stable morphologies. This paper argues that such convergence creates a morphology trap: actors may continue optimizing visible platform bodies after strategic advantage has shifted toward orchestration architectures and infrastructure control. It proposes a transition from control substitution, in which machines replace human operators, to structural dominance, in which power derives from coordinating, sustaining, and scaling autonomous ecosystems. The paper advances three propositions: platform morphology will increasingly converge; competitive advantage will migrate toward orchestration systems such as swarm coordination, distributed task allocation, and real-time integration; and long-term dominance will depend on control over compute, semiconductors, energy, manufacturing, logistics, and communication networks. The future of autonomous power will therefore be determined less by the sophistication of individual machines than by the infrastructures that allow autonomous systems to operate at scale.
Files
Mobile browsers may not display embedded PDF previews reliably. Open the PDF directly for the best reading experience.
Open PDF Download PDF| Name | Type | |
|---|---|---|
| From Control Substitution to Structural Dominance Beyond Morphology in the Age of Autonomous Systems.pdf Full-text PDF of the working paper | application/pdf | Download |
Keywords
- autonomous systems
- morphological convergence
- infrastructure power
- structural dominance
- distributed robotics
- swarm coordination
- system orchestration
- morphology trap
- control substitution
- morphological attractors
- autonomous platforms
- unmanned systems
- robotics
- drones
- unmanned aerial vehicles
- unmanned ground vehicles
- autonomous maritime systems
- infrastructure-dependent ecosystems
- compute infrastructure
- semiconductors
- energy systems
- manufacturing capacity
- communication networks
- logistics
- AI governance
- strategic technology
- EPINOVA
Subjects
- Artificial intelligence
- AI governance
- Autonomous systems
- Robotics
- Strategic technology
- Infrastructure studies
- Systems engineering
- Defense innovation
- Technology policy
- Strategic competition
Recommended citation
Wu, Shaoyuan. (2026). From Control Substitution to Structural Dominance: Morphological Convergence and Infrastructure Power in Autonomous Systems (EPINOVA Working Paper No. EPINOVA–WP–A–2026–03). Global AI Governance and Policy Research Center, EPINOVA LLC. DOI: To be assigned after Crossref membership approval.
APA citation
Wu, S. (2026). From control substitution to structural dominance: Morphological convergence and infrastructure power in autonomous systems (EPINOVA Working Paper No. EPINOVA-WP-A-2026-03). Global AI Governance and Policy Research Center, EPINOVA LLC. DOI: To be assigned after Crossref membership approval.
Alternate identifiers
| Scheme | Identifier | Description |
|---|---|---|
| URL | https://epinova.org/working-papers | Official EPINOVA working papers page |
| EPINOVA working paper number | EPINOVA–WP–A–2026–03 | Working paper number printed in the PDF |
| File name | From Control Substitution to Structural Dominance Beyond Morphology in the Age of Autonomous Systems.pdf | Source PDF file name |
| Analytical concept | Structural Dominance | Core concept developed in the working paper |
| Analytical concept | Morphology Trap | Strategic misallocation condition introduced in the working paper |
| Analytical concept | Morphological Convergence | Core mechanism explaining convergence of autonomous-system platform bodies |
Related works
| Relation | Identifier | Type | Description |
|---|---|---|---|
| IsPartOf | https://epinova.org/working-papers | Publication series | EPINOVA Working Paper Series |
| IsSupplementedBy | https://github.com/EPINOVALLC/EPINOVA-Research | Repository | Supplementary repository and structural archive |
| References | Allen & Chan, 2017, Artificial Intelligence and National Security | Report | Referenced for AI, national security, and infrastructure implications of autonomy |
| References | Brambilla et al., 2013, Swarm Robotics: A Review from the Swarm Engineering Perspective | Journal article | Referenced for swarm robotics and distributed coordination |
| References | Farrell & Newman, 2019, Weaponized Interdependence | Journal article | Referenced for infrastructure and network-based structural power |
| References | Floreano & Wood, 2015, Science, Technology and the Future of Small Autonomous Drones | Journal article | Referenced for autonomous drone technology and platform constraints |
| References | Losos, 2017, Improbable Destinies | Book | Referenced for convergent evolution and morphological analogy |
References
- Allen, G. C., & Chan, T. (2017). Artificial intelligence and national security. Belfer Center for Science and International Affairs, Harvard Kennedy School. https://www.belfercenter.org/publication/artificial-intelligence-and-national-security
- Arquilla, J., & Ronfeldt, D. (2001). Networks and netwars: The future of terror, crime, and militancy. RAND Corporation. https://www.rand.org/pubs/monograph_reports/MR1382.html
- Barabási, A.-L. (2016). Network science. Cambridge University Press. https://networksciencebook.com
- Beni, G. (2005). From swarm intelligence to swarm robotics. In E. Şahin & W. M. Spears (Eds.), Swarm robotics (pp. 1–9). Springer. https://doi.org/10.1007/978-3-540-30552-1_1
- Brambilla, M., Ferrante, E., Birattari, M., & Dorigo, M. (2013). Swarm robotics: A review from the swarm engineering perspective. Swarm Intelligence, 7(1), 1–41. https://doi.org/10.1007/s11721-012-0075-2
- Brynjolfsson, E., & McAfee, A. (2017). Machine, platform, crowd: Harnessing our digital future. W. W. Norton. https://wwnorton.com/books/9780393254296
- Dorigo, M. (2020). Reflections on the future of swarm robotics. Science Robotics, 5(49), eabe4385. https://doi.org/10.1126/scirobotics.abe4385
- Farrell, H., & Newman, A. L. (2019). Weaponized interdependence: How global economic networks shape state coercion. International Security, 44(1), 42–79. https://doi.org/10.1162/isec_a_00351
- Floreano, D., & Wood, R. J. (2015). Science, technology and the future of small autonomous drones. Nature, 521, 460–466. https://doi.org/10.1038/nature14542
- Hamann, H. (2018). Swarm robotics: A formal approach. Springer. https://doi.org/10.1007/978-3-319-74528-2
- Holland, J. H. (2014). Complexity: A very short introduction. Oxford University Press. https://doi.org/10.1093/actrade/9780199662547.001.0001
- Horowitz, M. C. (2010). The diffusion of military power: Causes and consequences for international politics. Princeton University Press. https://press.princeton.edu/books/paperback/9780691143964/the-diffusion-of-military-power
- Horowitz, M. C., Kahn, L., & Mahoney, C. (2020). Artificial intelligence and international security. International Organization, 74(S1), E1–E16. https://doi.org/10.1017/S0020818320000166
- Johnson, J. (2023). Automating the OODA loop in the age of intelligent machines: Reaffirming the role of humans in command-and-control decision-making in the digital age. Defense Studies, 23(1), 43–67. https://doi.org/10.1080/14702436.2022.2102486
- Kott, A., & Alberts, D. S. (2017). How do you command an army of intelligent things? arXiv. https://arxiv.org/abs/1712.08976
- Laschi, C., Mazzolai, B., & Cianchetti, M. (2016). Soft robotics: Technologies and systems pushing the boundaries of robot abilities. Science Robotics, 1(1), eaah3690. https://doi.org/10.1126/scirobotics.aah3690
- Losos, J. B. (2017). Improbable destinies: Fate, chance, and the future of evolution. Riverhead Books. https://www.penguinrandomhouse.com/books/252877/improbable-destinies-by-jonathan-b-losos/
- McGhee, G. R. (2011). Convergent evolution: Limited forms most beautiful. MIT Press. https://mitpress.mit.edu/9780262016420/convergent-evolution/
- Murphy, R. R. (2014). Disaster robotics. MIT Press. https://mitpress.mit.edu/9780262525892/disaster-robotics/
- Scharre, P. (2018). Army of none: Autonomous weapons and the future of war. W. W. Norton. https://wwnorton.com/books/9780393608990
- Singer, P. W. (2009). Wired for war: The robotics revolution and conflict in the 21st century. Penguin Press. https://www.penguinrandomhouse.com/books/306515/wired-for-war-by-pw-singer/
- Watts, D. J. (2003). Six degrees: The science of a connected age. W. W. Norton. https://wwnorton.com/books/9780393325422