The DOI matches its Crossref record; 11 of the 11 references it cites were found in a registry or an index.
Experiments with the subsumption architecture
Abstract
The subsumption architecture (SA) is a special case of behavior-based control for robotics. Behavioral modules are added as 'layers', with each layer performing a complete behavior. Higher-level behaviors override lower level ones by taking control of their effectors or manipulating their internal states. The control layers are built of finite-state machines connected by links that act essentially like wires. A prototype airplane controller made with the architecture was developed. This controller flies a simulated aircraft from take-off to landing and was run on a C-based implementation of the subsumption architecture. It was noted that the SA as currently defined is not sufficiently modular, a clean interface between different behaviors would be desirable, and a more general relationship than strict hierarchy between high-level and low-level modules is required. None of these problems is insoluble within the behavior-based approach, but all must be solved if realistic problems are to be dealt with. Some candidate solutions are given.>
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“While very simple organisms may get by with a fixed lexical ordering over priorities [18], a fixed ordering lacks the flexibility needed to accommodate multiple context-sensitive demands [19,20].”
From Phenomenal interface theory: a model for basal consciousness (2025) · cites this paper as [19]
Citations
Cites
Genetic algorithms in search, optimization, and machine learning
(1989) · Choice Reviews Online · doi:10.5860/choice.27-0936 · Cited by 49,051
The Fractal Geometry of Nature
Mandelbrot, B. B., & WHEELER, J. A. (1983) · American Journal of Physics · doi:10.1119/1.13295 · Cited by 21,964
A robust layered control system for a mobile robot
Brooks, R. (1986) · IEEE Journal on Robotics and Automation · doi:10.1109/jra.1986.1087032 · Cited by 7,799
The Fractal Geometry of Nature
Mandelbrot, B. B., & Longley, P. (1982) · CERN Document Server (European Organization for Nuclear Research) · Cited by 7,293
Motor Schema — Based Mobile Robot Navigation
Arkin, R. C. (1989) · The International Journal of Robotics Research · doi:10.1177/027836498900800406 · Cited by 998
Achieving Artificial Intelligence through Building Robots
Brooks, R. A. (1986) · Defense Technical Information Center (DTIC) · Cited by 304
A Robust Layered Control System for a Mobile Robot
(1999) · The MIT Press eBooks · doi:10.7551/mitpress/1716.003.0003 · Cited by 286
Ethology: The Mechanisms and Evolution of Behavior
Gould, J. L. (1982) · Medical Entomology and Zoology · Cited by 193
Jaskiw, G. E. (1987) · American Journal of Psychiatry · doi:10.1176/ajp.144.9.1233-a · Cited by 138
A behavior-based arm controller
Connell, J. H. (1989) · IEEE Transactions on Robotics and Automation · doi:10.1109/70.88099 · Cited by 111
Cited by
Phenomenal interface theory: a model for basal consciousness
Klein, C., & Barron, A. B. (2025) · Philosophical Transactions of the Royal Society B: Biological Sciences · doi:10.1098/rstb.2024.0301 · Cited by 8
“While very simple organisms may get by with a fixed lexical ordering over priorities [18], a fixed ordering lacks the flexibility needed to accommodate multiple context-sensitive demands [19,20].”
Metadata
- Authors
- Hartley, R., & Pipitone, F.
- Affiliations
- United States Naval Research Laboratory (US)
- Venue
- Proceedings. 1991 IEEE International Conference on Robotics and Automation
- Publisher
- IEEE Comput. Soc. Press
- Published
- 2002-12-10
- Pages
- 1652-1658
- ISSN
- 1050-4729 (ISSN-L)
- OpenAlex
- W2142136660
- Cited by
- 68
- References
- 11
- Citations by year
- 2025: 19 · 2022: 2 · 2021: 1 · 2019: 1 · 2017: 1 · 2016: 1 · 2015: 1 · 2014: 1 · 2013: 1
- FWCI
- 4.07
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- Proceedings - IEEE International Conference on Robotics and Automation/Proceedings (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › AI-based Problem Solving and Planning
- Physical Sciences › Computer Science › Artificial Intelligence › Psychiatry, Mental Health, Neuroscience
- Physical Sciences › Computer Science › Artificial Intelligence › Reinforcement Learning in Robotics
- Keywords
- subsumption architecture, behavior-based control, robotics, layered control, finite automata, flight simulation, autonomous flight control
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
