Abstract
| Original language | English |
|---|---|
| Title of host publication | Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence |
| Subtitle of host publication | AAAI Technical Track: Planning, Routing, and Scheduling |
| Place of Publication | Menlo Park, US-CA. |
| Number of pages | 8 |
| Volume | 33 |
| DOIs | |
| Publication status | Published - 1 Feb 2019 |
| Event | Thirty-Third AAAI Conference on Artificial Intelligence (AAAI-19) - Honolulu, United States Duration: 27 Jan 2019 → 1 Feb 2019 |
Conference
| Conference | Thirty-Third AAAI Conference on Artificial Intelligence (AAAI-19) |
|---|---|
| Abbreviated title | AAAI-19 |
| Country | United States |
| City | Honolulu |
| Period | 27/01/19 → 1/02/19 |
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Keywords
- simple temporal networks (STN)
- temporal plans
Cite this
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Robustness envelopes for temporal plans. / Cashmore, Michael; Cimatti, Alessandro; Magazzeni, Daniele; Micheli, Andrea; Zehtabi, Parisa.
Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence : AAAI Technical Track: Planning, Routing, and Scheduling . Vol. 33 Menlo Park, US-CA., 2019. 6285.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution book
TY - GEN
T1 - Robustness envelopes for temporal plans
AU - Cashmore, Michael
AU - Cimatti, Alessandro
AU - Magazzeni, Daniele
AU - Micheli, Andrea
AU - Zehtabi, Parisa
PY - 2019/2/1
Y1 - 2019/2/1
N2 - To achieve practical execution, planners must produce temporal plans with some degree of run-time adaptability. Such plans can be expressed as Simple Temporal Networks (STN), that constrain the timing of action activations, and implicitly represent the space of choices for the plan executor. A first problem is to verify that all the executor choices allowed by the STN plan will be successful, i.e. the plan is valid. An even more important problem is to assess the effect of discrepancies between the model used for planning and the execution environment. We propose an approach to compute the 'robustness envelope' (i.e., alternative action durations or resource consumption rates) of a given STN plan, for which the plan remains valid. Plans can have boolean and numeric variables as well as discrete and continuous change. We leverage Satisfiability Modulo Theories (SMT) to make the approach formal and practical.
AB - To achieve practical execution, planners must produce temporal plans with some degree of run-time adaptability. Such plans can be expressed as Simple Temporal Networks (STN), that constrain the timing of action activations, and implicitly represent the space of choices for the plan executor. A first problem is to verify that all the executor choices allowed by the STN plan will be successful, i.e. the plan is valid. An even more important problem is to assess the effect of discrepancies between the model used for planning and the execution environment. We propose an approach to compute the 'robustness envelope' (i.e., alternative action durations or resource consumption rates) of a given STN plan, for which the plan remains valid. Plans can have boolean and numeric variables as well as discrete and continuous change. We leverage Satisfiability Modulo Theories (SMT) to make the approach formal and practical.
KW - simple temporal networks (STN)
KW - temporal plans
U2 - 10.1609/aaai.v33i01.33017538
DO - 10.1609/aaai.v33i01.33017538
M3 - Conference contribution book
VL - 33
BT - Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence
CY - Menlo Park, US-CA.
ER -