Flexible Execution of Plans with Choice
Dynamic plan execution strategies allow an autonomous agent to respond to uncertainties while improving robustness and reducing the need for an overly conservative plan. Executives have improved this robustness by expanding the types of choices made dynamically, such as selecting alternate meth...
| Main Authors: | , , |
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| Other Authors: | |
| Format: | Article |
| Language: | en_US |
| Published: |
Association for the Advancement of Artificial Intelligence
2010
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| Online Access: | http://hdl.handle.net/1721.1/59432 https://orcid.org/0000-0002-1057-3940 https://orcid.org/0000-0003-1338-8107 |
| _version_ | 1811082618464108544 |
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| author | Williams, Brian Charles Conrad, Patrick Raymond Shah, Julie A. |
| author2 | Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory |
| author_facet | Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory Williams, Brian Charles Conrad, Patrick Raymond Shah, Julie A. |
| author_sort | Williams, Brian Charles |
| collection | MIT |
| description | Dynamic plan execution strategies allow an autonomous
agent to respond to uncertainties while improving
robustness and reducing the need for an overly
conservative plan. Executives have improved this robustness
by expanding the types of choices made dynamically,
such as selecting alternate methods. However,
in methods to date, these additional choices introduce
substantial run-time latency. This paper presents a
novel system called Drake that makes steps towards executing
an expanded set of choices dynamically without
significant latency.
Drake frames a plan as a Disjunctive Temporal Problem
and executes it with a fast dynamic scheduling algorithm.
Prior work demonstrated an efficient technique
for dynamic execution of one special type of DTPs by
using an off-line compilation step to find the possible
consistent choices and compactly record the differences
between them. Drake extends this work to handle a
more general set of choices by recording the minimal
differences between the solutions which are required at
run-time. On randomly generated structured plans with
choice, we show a reduction in the size of the solution
set of over two orders of magnitude, compared to prior
art. |
| first_indexed | 2024-09-23T12:06:16Z |
| format | Article |
| id | mit-1721.1/59432 |
| institution | Massachusetts Institute of Technology |
| language | en_US |
| last_indexed | 2024-09-23T12:06:16Z |
| publishDate | 2010 |
| publisher | Association for the Advancement of Artificial Intelligence |
| record_format | dspace |
| spelling | mit-1721.1/594322022-09-28T00:09:25Z Flexible Execution of Plans with Choice Williams, Brian Charles Conrad, Patrick Raymond Shah, Julie A. Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory Massachusetts Institute of Technology. Department of Aeronautics and Astronautics Williams, Brian Charles Williams, Brian Charles Conrad, Patrick Raymond Shah, Julie A. Dynamic plan execution strategies allow an autonomous agent to respond to uncertainties while improving robustness and reducing the need for an overly conservative plan. Executives have improved this robustness by expanding the types of choices made dynamically, such as selecting alternate methods. However, in methods to date, these additional choices introduce substantial run-time latency. This paper presents a novel system called Drake that makes steps towards executing an expanded set of choices dynamically without significant latency. Drake frames a plan as a Disjunctive Temporal Problem and executes it with a fast dynamic scheduling algorithm. Prior work demonstrated an efficient technique for dynamic execution of one special type of DTPs by using an off-line compilation step to find the possible consistent choices and compactly record the differences between them. Drake extends this work to handle a more general set of choices by recording the minimal differences between the solutions which are required at run-time. On randomly generated structured plans with choice, we show a reduction in the size of the solution set of over two orders of magnitude, compared to prior art. 2010-10-20T19:15:18Z 2010-10-20T19:15:18Z 2009-09 Article http://purl.org/eprint/type/ConferencePaper http://hdl.handle.net/1721.1/59432 Conrad, Patrick R., Julie A. Shah, and Brian C. Williams. "Flexible Execution of Plans with Choice." Proceedings of the Nineteenth International Conference on Automated Planning and Scheduling, Thessaloniki, Greece September 19, 2009–September 23, 2009. https://orcid.org/0000-0002-1057-3940 https://orcid.org/0000-0003-1338-8107 en_US 19th International Conference on Automated Planning and Scheduling Attribution-Noncommercial-Share Alike 3.0 Unported http://creativecommons.org/licenses/by-nc-sa/3.0/ application/pdf Association for the Advancement of Artificial Intelligence MIT web domain |
| spellingShingle | Williams, Brian Charles Conrad, Patrick Raymond Shah, Julie A. Flexible Execution of Plans with Choice |
| title | Flexible Execution of Plans with Choice |
| title_full | Flexible Execution of Plans with Choice |
| title_fullStr | Flexible Execution of Plans with Choice |
| title_full_unstemmed | Flexible Execution of Plans with Choice |
| title_short | Flexible Execution of Plans with Choice |
| title_sort | flexible execution of plans with choice |
| url | http://hdl.handle.net/1721.1/59432 https://orcid.org/0000-0002-1057-3940 https://orcid.org/0000-0003-1338-8107 |
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