Faster Dynamic-Consistency Checking for Conditional Simple Temporal Networks

Hunsberger, Luke; Posenato, Roberto

doi:10.1609/icaps.v30i1.6656

Cited by 2 publications

(4 citation statements)

References 5 publications

(10 reference statements)

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“…Morris14 is the DC-checking algorithm proposed by Morris (2014), which we modified according to his high-level description to enable it to generate equivalent dispatchable networks. FD STNU is the fast dispatchable STNU algorithm presented by Hunsberger and Posenato (2023).…”

Section: Empirical Evaluationmentioning

confidence: 99%

“…We call that version of his algorithm Morris14. More recently, Hunsberger and Posenato (2023) presented an algorithm for creating an equivalent dispatchable STNU called FD STNU . Although these are the only known algorithms that guarantee an equivalent dispatchable output, they do not make any claims about the number of edges in the output.…”

Section: Introduction and Related Workmentioning

confidence: 99%

“…However, as Morris (2014) noted, his O(n 3 )time DC-checking algorithm can be modified to generate waits and, in doing so, guarantee an equivalent dispatchable output. More recently, Hunsberger and Posenato (2023) presented a faster algorithm for generating equivalent dispatchable ESTNUs. However, neither algorithm makes any claim about the number of edges in the dispatchable output.…”

Section: Introductionmentioning

confidence: 99%

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Converting Simple Temporal Networks with Uncertainty into Minimal Equivalent Dispatchable Form

Hunsberger,

Posenato

2024

ICAPS

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A Simple Temporal Network with Uncertainty (STNU) is a structure for representing and reasoning about time constraints on actions that may have uncertain durations. An STNU is dynamically controllable (DC) if there exists a dynamic strategy for executing the network that guarantees that all of its constraints will be satisfied no matter how the uncertain durations turn out---within their specified bounds. However, such strategies typically require exponential space. Therefore, converting a DC STNU into a so-called dispatchable form for practical applications is essential. The relevant portions of a real-time execution strategy for a dispatchable STNU can be incrementally constructed during execution, requiring only O(n²) space, while also providing maximum flexibility and minimal computation during the execution of the network. Although existing algorithms can generate equivalent-dispatchable STNUs, they do not guarantee a minimal number of edges in the STNU graph. Since the number of edges directly impacts the computations during execution, this paper presents a novel algorithm for converting any dispatchable STNU into an equivalent dispatchable network having a minimal number of edges. The complexity of the algorithm is O(k n³), where k is the number of actions with uncertain durations, and n is the number of timepoints in the network. The paper also provides an empirical evaluation of the reduction of edges obtained by the impact of the new algorithm.

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Section: Empirical Evaluationmentioning

confidence: 99%

Section: Introduction and Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Converting Simple Temporal Networks with Uncertainty into Minimal Equivalent Dispatchable Form

Hunsberger,

Posenato

2024

ICAPS

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“…For instance, Conrad and Williams (2011) and respectively study STN with choices and with decisions, where the executor might have the choice between several set of requirement constraints. In the context of Conditional STNs, Hunsberger and Posenato (2020) instead focus on determining the dynamic controllability of networks where requirement constraints are activated as a result of contingent observations made at runtime. Combi et al (2014) consider the introduction of temporal uncertainty in Conditional STNs, which is further extended with runtime decision points by .…”

Section: Other Stn Extensionsmentioning

confidence: 99%

Dynamic Controllability of Temporal Plans in Uncertain and Partially Observable Environments

Bit-Monnot

Morris

2023

jair

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The formalism of Simple Temporal Networks (STNs) provides methods for evaluating the feasibility of temporal plans. The basic formalism deals with the consistency of quantitative temporal requirements on scheduled events. This implicitly assumes a single agent has full control over the timing of events. The extension of Simple Temporal Networks with Uncertainty (STNU) introduces uncertainty into the timing of some events. Two main approaches to the feasibility of STNUs involve (1) where a single schedule works irrespective of the duration outcomes, called Strong Controllability, and (2) whether a strategy exists to schedule future events based on the outcomes of past events, called Dynamic Controllability. Case (1) essentially assumes the timing of uncertain events cannot be observed by the agent while case (2) assumes full observability. The formalism of Partially Observable Simple Temporal Networks with Uncertainty (POSTNU) provides an intermediate stance between these two extremes, where a known subset of the uncertain events can be observed when they occur. A sound and complete polynomial algorithm to determining the Dynamic Controllability of POSTNUs has not previously been known; we present one in this paper. This answers an open problem that has been posed in the literature. The approach we take factors the problem into Strong Controllability micro-problems in an overall Dynamic Controllability macro-problem framework. It generalizes the notion of labeled distance graph from STNUs. The generalized labels are expressed as max/min expressions involving the observables. The paper introduces sound generalized reduction rules that act on the generalized labels. These incorporate tightenings based on observability that preserve dynamic viable strategies. It is shown that if the generalized reduction rules reach quiescence without exposing an inconsistency, then the POSTNU is Dynamically Controllable (DC). The paper also presents algorithms that apply the reduction rules in an organized way and reach quiescence in a polynomial number of steps if the POSTNU is Dynamically Controllable. Remarkably, the generalized perspective leads to a simpler and more uniform framework that applies also to the STNU special case. It helps illuminate the previous methods inasmuch as the max/min label representation is more semantically clear than the ad-hoc upper/lower case labels previously used.

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Faster Dynamic-Consistency Checking for Conditional Simple Temporal Networks

Cited by 2 publications

References 5 publications

Converting Simple Temporal Networks with Uncertainty into Minimal Equivalent Dispatchable Form

Converting Simple Temporal Networks with Uncertainty into Minimal Equivalent Dispatchable Form

Dynamic Controllability of Temporal Plans in Uncertain and Partially Observable Environments

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