Principles for Engineered Emergence (slides)
Principles for Engineered EmergenceIt is difficult to establish engineering control over the behavior ofaggregates of unreliable devices with complicated interactionpatterns. I take a linguistic view of this problem, searching formechanisms that simplify the composition and abstraction ofcomplicate...
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2007
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| Online Access: | http://hdl.handle.net/1721.1/37152 |
| _version_ | 1811098078307942400 |
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| author | Beal, Jacob |
| author2 | Gerald Sussman |
| author_facet | Gerald Sussman Beal, Jacob |
| author_sort | Beal, Jacob |
| collection | MIT |
| description | Principles for Engineered EmergenceIt is difficult to establish engineering control over the behavior ofaggregates of unreliable devices with complicated interactionpatterns. I take a linguistic view of this problem, searching formechanisms that simplify the composition and abstraction ofcomplicated behaviors. From my work on various problems of aggregatecontrol in cognitive architectures and spatial computing, I havenoticed common themes in mechanisms that solve them. From these, Iextract four principles which seem to help in engineering robustaggregate behavior---self-scaling, sparseness, gradual degradation,and failure simplification---and give examples of how they can beexploited. |
| first_indexed | 2024-09-23T17:09:34Z |
| id | mit-1721.1/37152 |
| institution | Massachusetts Institute of Technology |
| last_indexed | 2024-09-23T17:09:34Z |
| publishDate | 2007 |
| record_format | dspace |
| spelling | mit-1721.1/371522019-04-12T07:40:31Z Principles for Engineered Emergence (slides) Beal, Jacob Gerald Sussman Mathematics and Computation artificial intelligence amorphous computing Principles for Engineered EmergenceIt is difficult to establish engineering control over the behavior ofaggregates of unreliable devices with complicated interactionpatterns. I take a linguistic view of this problem, searching formechanisms that simplify the composition and abstraction ofcomplicated behaviors. From my work on various problems of aggregatecontrol in cognitive architectures and spatial computing, I havenoticed common themes in mechanisms that solve them. From these, Iextract four principles which seem to help in engineering robustaggregate behavior---self-scaling, sparseness, gradual degradation,and failure simplification---and give examples of how they can beexploited. 2007-04-12T20:21:45Z 2007-04-12T20:21:45Z 2007-04-12 http://hdl.handle.net/1721.1/37152 Massachusetts Institute of Technology Computer Science and Artificial Intelligence Laboratory 28 p. application/pdf |
| spellingShingle | artificial intelligence amorphous computing Beal, Jacob Principles for Engineered Emergence (slides) |
| title | Principles for Engineered Emergence (slides) |
| title_full | Principles for Engineered Emergence (slides) |
| title_fullStr | Principles for Engineered Emergence (slides) |
| title_full_unstemmed | Principles for Engineered Emergence (slides) |
| title_short | Principles for Engineered Emergence (slides) |
| title_sort | principles for engineered emergence slides |
| topic | artificial intelligence amorphous computing |
| url | http://hdl.handle.net/1721.1/37152 |
| work_keys_str_mv | AT bealjacob principlesforengineeredemergenceslides |