ESD.83 Doctoral Seminar in Engineering Systems, Fall 2009
In establishing the Engineering Systems Division, MIT has embarked on a bold experiment – bringing together diverse areas of expertise into what is designed to be a new field of study. In many respects, the full scale and scope of Engineering Systems as a field is still emerging. This semi...
| Main Authors: | , |
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| Language: | en-US |
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2009
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| Online Access: | http://hdl.handle.net/1721.1/75814 |
| _version_ | 1811095219819511808 |
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| author | Magee, Christopher L. Sussman, Joseph |
| author_facet | Magee, Christopher L. Sussman, Joseph |
| author_sort | Magee, Christopher L. |
| collection | MIT |
| description | In establishing the Engineering Systems Division, MIT has embarked on a bold experiment – bringing together diverse areas of expertise into what is designed to be a new field of study. In many respects, the full scale and scope of Engineering Systems as a field is still emerging. This seminar is simultaneously designed to codify what we presently know and to give direction for future development. |
| first_indexed | 2024-09-23T16:12:44Z |
| id | mit-1721.1/75814 |
| institution | Massachusetts Institute of Technology |
| language | en-US |
| last_indexed | 2024-09-23T16:12:44Z |
| publishDate | 2009 |
| record_format | dspace |
| spelling | mit-1721.1/758142019-09-12T10:05:31Z ESD.83 Doctoral Seminar in Engineering Systems, Fall 2009 Doctoral Seminar in Engineering Systems Magee, Christopher L. Sussman, Joseph engineering systems complexity uncertainty fragility robustness systems engineering systems dynamics agent modeling systems simulations large-scale systems change modeling paradigms cumulative knowledge empirical data generation boundary setting network models policy evaluation In establishing the Engineering Systems Division, MIT has embarked on a bold experiment – bringing together diverse areas of expertise into what is designed to be a new field of study. In many respects, the full scale and scope of Engineering Systems as a field is still emerging. This seminar is simultaneously designed to codify what we presently know and to give direction for future development. 2009-12 ESD.83-Fall2009 local: ESD.83 local: IMSCP-MD5-adb5f81d26a181a0b37dd33875fe1340 http://hdl.handle.net/1721.1/75814 en-US Usage Restrictions: This site (c) Massachusetts Institute of Technology 2012. Content within individual courses is (c) by the individual authors unless otherwise noted. The Massachusetts Institute of Technology is providing this Work (as defined below) under the terms of this Creative Commons public license ("CCPL" or "license") unless otherwise noted. The Work is protected by copyright and/or other applicable law. Any use of the work other than as authorized under this license is prohibited. By exercising any of the rights to the Work provided here, You (as defined below) accept and agree to be bound by the terms of this license. The Licensor, the Massachusetts Institute of Technology, grants You the rights contained here in consideration of Your acceptance of such terms and conditions. text/html Fall 2009 |
| spellingShingle | engineering systems complexity uncertainty fragility robustness systems engineering systems dynamics agent modeling systems simulations large-scale systems change modeling paradigms cumulative knowledge empirical data generation boundary setting network models policy evaluation Magee, Christopher L. Sussman, Joseph ESD.83 Doctoral Seminar in Engineering Systems, Fall 2009 |
| title | ESD.83 Doctoral Seminar in Engineering Systems, Fall 2009 |
| title_full | ESD.83 Doctoral Seminar in Engineering Systems, Fall 2009 |
| title_fullStr | ESD.83 Doctoral Seminar in Engineering Systems, Fall 2009 |
| title_full_unstemmed | ESD.83 Doctoral Seminar in Engineering Systems, Fall 2009 |
| title_short | ESD.83 Doctoral Seminar in Engineering Systems, Fall 2009 |
| title_sort | esd 83 doctoral seminar in engineering systems fall 2009 |
| topic | engineering systems complexity uncertainty fragility robustness systems engineering systems dynamics agent modeling systems simulations large-scale systems change modeling paradigms cumulative knowledge empirical data generation boundary setting network models policy evaluation |
| url | http://hdl.handle.net/1721.1/75814 |
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