Name
Abstract | ||
|---|---|---|
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. |
Year | Venue | Field |
|---|---|---|
2019 | THIRTY-THIRD AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE / THIRTY-FIRST INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE CONFERENCE / NINTH AAAI SYMPOSIUM ON EDUCATIONAL ADVANCES IN ARTIFICIAL INTELLIGENCE | Resource consumption,Adaptability,Mathematical optimization,Leverage (finance),Executor,Computer science,Robustness (computer science),Boolean algebra,Satisfiability modulo theories |
DocType | Citations | PageRank |
Conference | 0 | 0.34 |
References | Authors | |
0 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Cashmore Michael | 1 | 64 | 10.30 |
| Alessandro Cimatti | 2 | 5064 | 323.15 |
| Magazzeni Daniele | 3 | 249 | 32.82 |
| Andrea Micheli | 4 | 190 | 14.08 |
| Parisa Zehtabi | 5 | 1 | 0.71 |