Efficient processing of simple temporal networks with uncertainty: algorithms for dynamic controllability verification

Nilsson, Mikael; Kvarnström, Jonas; Doherty, Patrick

doi:10.1007/s00236-015-0248-8

Cited by 4 publications

(3 citation statements)

References 10 publications

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“…An STNU is said to be Dynamically Controllable (Hunsberger, 2009;Morris et al, 2001;Morris, 2014;Vidal & Fargier, 1999) if there is a strategy for scheduling each executable timepoint that depends only on observations that are available in the past or present at the time it is scheduled. 1 Whether an STNU is Dynamically Controllable or not can be determined by algorithms that run in cubic time (Cairo et al, 2018;Cairo & Rizzi, 2017;Morris, 2014;Nilsson et al, 2015).…”

Section: Stnumentioning

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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Section: Stnumentioning

confidence: 99%

Dynamic Controllability of Temporal Plans in Uncertain and Partially Observable Environments

Bit-Monnot

Morris

2023

jair

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“…We now add initial support for actions with uncontrollable durations, using E2IDC (Nilsson, Kvarnström, and Doherty 2016) to incrementally verify dynamic controllability.…”

Section: Tfpop With Uncontrollable Durationsmentioning

confidence: 99%

Planning with Temporal Uncertainty, Resources and Non-Linear Control Parameters

Nilsson

Kvarnström

Doherty

2018

ICAPS

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We consider a general and industrially motivated class of planning problems involving a combination of requirements that can be essential to autonomous robotic systems planning to act in the real world: Support for temporal uncertainty where nature determines the eventual duration of an action, resource consumption with a non-linear relationship to durations, and the need to select appropriate values for control parameters that affect time requirements and resource usage. To this end, an existing planner is extended with support for Simple Temporal Networks with Uncertainty, Timed Initial Literals, and temporal coverage goals. Control parameters are lifted from the main combinatorial planning problem into a constraint satisfaction problem that connects them to resource usage. Constraint processing is then integrated and interleaved with verification of temporal feasibility, using projections for partial temporal awareness in the constraint solver.

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“…(Note that a wait or conditional edge reduces to an ordinary edge in each projection (Morris 2014). ) Reduction rules in recent STNU work (Shah et al 2007;Nilsson, Kvarnström, and Doherty 2013;Morris 2014;Nilsson, Kvarnström, and Doherty 2015) involve "plus-minus" rules where a non-negative AB edge followed by a BC negative edge may result in an added AC edge. It is not difficult to see that applying "plus-minus" transformation rules repeatedly to a shortest path will eventually result in a veepath where all the remaining negative edges precede all the remaining non-negative edges.…”

Section: Temporal Uncertaintymentioning

confidence: 99%

The Mathematics of Dispatchability Revisited

Morris

2016

ICAPS

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Dispatchability is an important property for the efficient execution of temporal plans where the temporal constraints are represented as a Simple Temporal Network (STN). It has been shown that every STN may be reformulated as a dispatchable STN, and dispatchability ensures that the temporal constraints need only be satisfied locally during execution. Recently it has also been shown that Simple Temporal Networks with Uncertainty, augmented with wait edges, are Dynamically Controllable provided every projection is dispatchable. Thus, the dispatchability property has both theoretical and practical interest. One thing that hampers further work in this area is the under-developed theory. The existing definitions are expressed in terms of algorithms, and are less suitable for mathematical proofs. In this paper, we develop a new formal theory of dispatchability in terms of execution sequences. We exploit this to prove a characterization of dispatchability involving the structural properties of the STN graph. This facilitates the potential application of the theory to uncertainty reasoning.

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Efficient processing of simple temporal networks with uncertainty: algorithms for dynamic controllability verification

Cited by 4 publications

References 10 publications

Dynamic Controllability of Temporal Plans in Uncertain and Partially Observable Environments

Dynamic Controllability of Temporal Plans in Uncertain and Partially Observable Environments

Planning with Temporal Uncertainty, Resources and Non-Linear Control Parameters

The Mathematics of Dispatchability Revisited

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