Artificial states generation in state spaces using kernel density estimation
From LRDE
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- Authors
- Thomas De Carvalho
- Type
- techreport
- Year
- 2019
- Number
- 1916
Abstract
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.