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2020-12-01T12:31:04+01:00
Artificial states generation in state spaces using kernel density estimation
0
en
The objective is to improve Spot, a model checking library. Spot deals with a specific kind of graph in which each state is a set of variables with given values. These values can be seen as coordinates and a state can therefore be seen as a N-dimensional point. The state space is then a N-dimensional cloud and Spot does a depth first search on it. We want to generate states on the fly to improve the performances. For that, we use a kernel probability density estimation. The generated states are then used as starting points for threads which will explore the state space in parallel.
1916
Thomas De Carvalho
carvalho.19.seminar
Artificial states generation in state spaces using kernel density estimation
techreport
2019
Artificial states generation in state spaces using kernel density estimation
2019-06-27T17:53:53Z
2458662.2457523
Artificial states generation in state spaces using kernel density estimation