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2015 | OriginalPaper | Chapter

New Techniques for Checking Dynamic Controllability of Simple Temporal Networks with Uncertainty

Author : Luke Hunsberger

Published in: Agents and Artificial Intelligence

Publisher: Springer International Publishing

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Abstract

A Simple Temporal Network with Uncertainty (STNU) is a structure for representing time-points, temporal constraints, and temporal intervals with uncertain—but bounded—durations. The most important property of an STNU is whether it is dynamically controllable (DC)—that is, whether there exists a strategy for executing its time-points such that all constraints will necessarily be satisfied no matter how the uncertain durations turn out. Algorithms for checking from scratch whether STNUs are dynamically controllable are called (full) DC-checking algorithms. Algorithms for checking whether the insertion of one new constraint into an STNU preserves its dynamic controllability are called incremental DC-checking algorithms. This paper introduces novel techniques for speeding up both full and incremental DC checking. The first technique, called rotating Dijkstra, enables constraints generated by propagation to be immediately incorporated into the network. The second uses novel heuristics that exploit the nesting structure of certain paths in STNU graphs to determine good orders in which to propagate constraints. The third technique, which only applies to incremental DC checking, maintains information acquired from previous invocations to reduce redundant computation. The most important contribution of the paper is the incremental algorithm, called Inky, that results from using these techniques. Like its fastest known competitors, Inky is a cubic-time algorithm. However, a comparative empirical evaluation of the top incremental algorithms, all of which have only very recently appeared in the literature, must be left to future work.

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Footnotes
1
Agents are not part of the semantics of STNUs. They are used here for expository convenience.
 
2
The rules are shown using Morris and Muscettola’s notation. Note that: the x’s and y’s here are not necessarily bounds for contingent links; C is only required to be contingent in the Lower Case and Cross Case rules, where its activation time-point is D and its lower bound is y; and in the Upper Case and Cross Case rules, B is contingent, with activation time-point A. The Lower Case rule only applies when \(x \le 0\) and \(A \ne C\); the Cross Case rule only applies when \(x \le 0\) and \(B \ne C\); and the Label Removal rule only applies when \(z \ge -x\).
 
3
A breach edge could prevent application of the Cross Case rule.
 
4
This conclusion is justified by Morris’ Theorem 3 that an STNU contains a semi-reducible negative loop if and only if it contains a breach-free semi-reducible negative loop in which the extension sub-paths are nested to a depth of at most K [8].
 
5
This follows immediately from how new edges are generated [8]. In particular, each new edge is generated by reducing the path consisting of the lower-case edge, https://static-content.springer.com/image/chp%3A10.1007%2F978-3-319-25210-0_11/371677_1_En_11_IEq193_HTML.gif , and some extension sub-path into a single new edge. Since such a reduction preserves the endpoints of the path, the generated edge must have A as its source.
 
6
This termination condition is analogous to the Morris-\(N^4\) algorithm terminating after K iterations of the outer loop.
 
7
This termination condition is analogous to the Morris-\(N^4\) algorithm terminating whenever any iteration of the outer loop fails to generate a new edge.
 
8
Any suffix of a breach-free extension sub-path is necessarily semi-reducible [5].
 
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Metadata
Title
New Techniques for Checking Dynamic Controllability of Simple Temporal Networks with Uncertainty
Author
Luke Hunsberger
Copyright Year
2015
DOI
https://doi.org/10.1007/978-3-319-25210-0_11

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