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@inproceedings{kim-hscc16,
author = {Eric S. Kim and Murat Arcak and Sanjit A. Seshia},
title = {Directed Specifications and Assumption Mining for Monotone Dynamical Systems},
booktitle = {Proceedings of the 9th International Conference on Hybrid Systems: Computation and Control (HSCC)},
month = "April",
year = {2016},
OPTpages = {239--248},
abstract = {Given a dynamical system and a specification, assumption
mining is the problem of identifying the set of admissible
disturbance signals and initial states that generate
trajectories satisfying the specification. We first introduce the
notion of a directed specification, which describes either upper
or lower sets in a partially ordered signal space, and show
that this notion encompasses an expressive temporal logic
fragment. We next show that the order preserving nature
of monotone dynamical systems makes them amenable to a
systematic form of assumption mining that checks numerical
simulations of system trajectories against directed
specifications. The assumption set is then located with a
multidimensional bisection method that converges to the boundary
from above and below. Typical objectives in vehicular traffic
control, such as avoiding or clearing congestion, are directed
specifications. In an application to a freeway flow model
with monotone dynamics, we identify the set of vehicular
demand profiles that satisfy a specification that congestion
be intermittent.},
}