Abstract
Many modern-day systems rely on information that is constantly arriving, and they need to make decisions based on it – a problem known as continuous query answering. In many situations, these systems can benefit from identifying possible outcomes that are consistent with the data available so far. Such scenarios are called hypothetical answers, and previous work has defined them precisely and shown how they can be updated in step with the arrival of additional input. Most existing formalisms assume that data always arrives instantaneously, which is not realistic. In this work, we relax this problem by allowing data to arrive later, and potentially out of order. By revisiting the underlying intuitions in previous work, we develop a more general framework that supports communication delays. The interaction between communication delays and negation poses some challenging problems, which we address using fixpoint theory. We show that the relevant fixpoints can be computed in finite time by a carefully designed algorithm
| Original language | English |
|---|---|
| Article number | 5 |
| Journal | Annals of Mathematics and Artificial Intelligence |
| Volume | 93 |
| Issue number | 5 |
| Pages (from-to) | 727-758 |
| Number of pages | 32 |
| ISSN | 1012-2443 |
| DOIs | |
| Publication status | Published - 17 Jan 2025 |
| Externally published | Yes |
Keywords
- Communication delays
- Continuous query answering
- Negation-as-failure
- Temporal datalog
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