Abstract
One of the major limitations for the employment of model-based planning and scheduling in practical applications is the need of costly re-planning when an incongruence between the observed reality and the formal model is encountered during execution. Robustness Envelopes characterize the set of possible contingencies that a plan is able to address without re-planning, but their exact computation is extremely expensive; furthermore, general robustness envelopes are not amenable for efficient execution. In this paper, we present a novel, anytime algorithm to approximate Robustness Envelopes, making them scalable and executable. This is proven by an experimental analysis showing the efficiency of the algorithm, and by a concrete case study where the execution of robustness envelopes significantly reduces the number of re-plannings.
| Original language | English |
|---|---|
| Place of Publication | Ithica, N.Y. |
| Number of pages | 8 |
| Publication status | Published - 17 Nov 2019 |
Keywords
- cs.AI
- robustness envelopes
- planning and scheduling
- practical applications
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