Name
Abstract | ||
|---|---|---|
Incremental Contingency Planning is a framework that considers all potential failures in a plan and attempts to avoid them by incrementally adding contingency branches to the plan in order to improve the overall probability. The planner focuses its attempts on the higher probability outcomes. Precautionary planning is a form of incremental contingency planning that takes advantage of the speed of replanning for easy contingencies and only considers the unrecoverable outcomes in the plan. In this work, we present an approach to incrementally generating contingency branches to deal with uncertain outcomes. The main idea is to first generate a high probability non-branching seed plan, which is then augmented with contingency branches to handle the most critical outcomes. Any remaining outcomes are handled by runtime replanning. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1007/978-3-319-44636-3_22 | ADVANCES IN ARTIFICIAL INTELLIGENCE, CAEPIA 2016 |
DocType | Volume | ISSN |
Conference | 9868 | 0302-9743 |
Citations | PageRank | References |
1 | 0.38 | 6 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yolanda E.-Martín | 1 | 21 | 3.84 |
| María D. R-Moreno | 2 | 97 | 15.22 |
| David E. Smith | 3 | 947 | 120.00 |