LIPIcs.TIME.2018.9.pdf
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Extending Conditional Simple Temporal Networks with Partially Shrinkable Uncertainty
Authors
Carlo Combi 
,
Roberto Posenato
-
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Volume:
25th International Symposium on Temporal Representation and Reasoning (TIME 2018)
Series: Leibniz International Proceedings in Informatics (LIPIcs)
Conference: International Symposium on Temporal Representation and Reasoning (TIME) - License:
Creative Commons Attribution 3.0 Unported license
- Publication Date: 2018-10-08
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Carlo Combi and Roberto Posenato. Extending Conditional Simple Temporal Networks with Partially Shrinkable Uncertainty. In 25th International Symposium on Temporal Representation and Reasoning (TIME 2018). Leibniz International Proceedings in Informatics (LIPIcs), Volume 120, pp. 9:1-9:16, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)
https://doi.org/10.4230/LIPIcs.TIME.2018.9
Abstract
The proper handling of temporal constraints is crucial in many domains. As a particular challenge, temporal constraints must be also handled when different specific situations happen (conditional constraints) and when some event occurrences can be only observed at run time (contingent constraints). In this paper we introduce Conditional Simple Temporal Networks with Partially Shrinkable Uncertainty (CSTNPSUs), in which contingent constraints are made more flexible (guarded constraints) and they are also specified as conditional constraints. It turns out that guarded constraints require the ability to reason on both kinds of constraints in a seamless way. In particular, we discuss CSTNPSU features through a motivating example and, then, we introduce the concept of controllability for such networks and the related sound checking algorithm.
Subject Classification
ACM Subject Classification
- Computing methodologies → Temporal reasoning
- Computing methodologies → Planning under uncertainty
- Computing methodologies → Planning for deterministic actions
Keywords
- Conditional Simple Temporal Networks with Uncertainty
- Partial Shrinkable Temporal Constraint
- Dynamic Controllability
- Temporal Constraints
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