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On Expected Value Strong ControllabilityThe Probabilistic Simple Temporal Network (PSTN) generalizes Simple Temporal Networks with Uncertainty (STNUs) by introducing probability distributions over the timing of uncontrollable timepoints. PSTNs are controllable if there is a strategy to execute the controllable timepoints while bounding the risk of violating any constraint to a small value. If this risk bound can't be satisfied, PSTNs are not considered controllable. We introduce the Expected Value Probabilistic SimpleTemporal Network (EPSTN), which extends PSTNs by including a benefit to the satisfaction of temporal constraints. We study the problem of Expected Value Strong Controllability (EvSC) of EPSTNs, which seeks a schedule maximizing the expected value of satisfied constraints. We solve the EvSC problem by extending a previously developed linear program, combined with search over constraints to violate at execution time. We describe conditions under which the solution to this linear program is the maximum expected value schedule. We then show how to search for constraints to discard, using the linear program at the core of the search. While the general problem is shown to be exponential, we conclude by providing several methods to bound the complexity of search.
Document ID
20190027408
Acquisition Source
Ames Research Center
Document Type
Conference Paper
Authors
Frank, Jeremy D.
(NASA Ames Research Center Moffett Field, CA, United States)
Date Acquired
July 17, 2019
Publication Date
July 11, 2019
Subject Category
Cybernetics, Artificial Intelligence And Robotics
Report/Patent Number
ARC-E-DAA-TN63664
Meeting Information
Meeting: International Conference on Automated Planning and Scheduling (ICAPS 2019)
Location: Berkeley, CA
Country: United States
Start Date: July 11, 2019
End Date: July 15, 2019
Sponsors: National Science Foundation
Distribution Limits
Public
Copyright
Work of the US Gov. Public Use Permitted.
Technical Review
NASA Peer Committee
Keywords
Planning
Scheduling
Uncertainty
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