On the use of genetic algorithms for synthesis of signal temporal logic formulas

Date

2018-07-09

Author

Aydin, Sertac Kagan
Aydın Göl, Ebru

Metadata

Show full item record

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Item Usage Stats

201
views

0
downloads

In this work, we studied use of genetic algorithms to synthesize Signal Temporal Logic formulas from a labeled data set. In the synthesis problem, the goal is to generate the best STL formula representing the labeled signals in the set. To use genetic algoritms in this domain, the basic genetic algoritm processes are defined for STL formulas. The developed synthesis method produces a formula from the data set efficiently in a fully automated way. In particular, the proposed approach does not require an expert to write a template formulas. The findings of the paper are illustrated on a sample data set.

Subject Keywords

Formal methods, STL, requirement mining, Genetic algorithms, genetic algorithms

URI

https://hdl.handle.net/11511/36157

DOI

https://doi.org/10.1109/siu.2018.8404508

Collections

Department of Computer Engineering, Conference / Seminar

Suggestions

OpenMETU
Core

Optimization of the array geometry for direction finding Özaydın, Seval; Koç, Seyit Sencer; Tanık, Yalçın; Department of Electrical and Electronics Engineering (2003) In this thesis, optimization of the geometry of non-uniform arrays for direction finding yielding unambiguous results is studied. A measure of similarity between the array response vectors is defined. In this measure, the effects of antenna array geometry, source placements and antenna gains are included as variable parameters. Then, assuming that the antenna gains are known and constant, constraints on the similarity function are developed and described to result in unambiguous configurations and maximum r...
A method for chromosome handling of r-permutations of n-element set in genetic algorithms Üçoluk, Göktürk (1997-04-16) Combinatorial optimisation problems are in the domain of Genetic Algorithms (GA) interest. Unfortunately ordinary crossover and mutation operators cause problems for chromosome representations of permutations and some types of combinations. This is so because offsprings generated by means of the ordinary operators are of a great possibility no more valid chromosomes. A variety of methods and new operators that handle that sort of obscenities are introduced throughout the literature. A new method for represe...
Optimizing Parameters of Signal Temporal Logic Formulas with Local Search Aydin, Sertac Kagan; Aydın Göl, Ebru (2019-08-22) Signal temporal logic (STL) is a formal language for expressing temporal and real-time properties of real valued signals. In this paper, we study the problem of generating an STL formula from a labeled dataset. We propose a local search algorithm to synthesize parameters of a template formula. Starting from a random initial point, the parameter space is explored in the directions improving the formula evaluation. In addition, the local search method is integrated to the genetic algorithms developed for form...
Optimizations of antennas using heuristic algorithms supported by the multilevel fast multipole algorithm Önol, Can; Ergül, Özgür Salih; Department of Electrical and Electronics Engineering (2015) In this study, an optimization environment based on heuristic algorithms supported by the multilevel fast multipole algorithm (MLFMA) is presented for different antenna problems involving either excitation or geometry optimizations. The heuristic algorithms are implemented in-house by aiming more effective interactions between electromagnetic solvers and optimization algorithms, instead of black box interactions. Excitation optimizations of various array geometries for desired radiation characteristics are ...
A Unified approach for center-based clustering problems on networks Eroğlu, Derya İpek; İyigün, Cem; Department of Industrial Engineering (2018) In this thesis, Center-Based Clustering Problems on Networks are studied. Four different problems are considered differing in the assignment scheme of the data points and the objective function. Two different assignment schemes are considered, hard assignment and soft assignment. In hard assignment, data points (vertices) are strictly assigned to one cluster, while in soft assignment, vertices are assigned to the multiple clusters with a membership probability. Objective function of a clustering problem cou...

Citation Formats

S. K. Aydin and E. Aydın Göl, “On the use of genetic algorithms for synthesis of signal temporal logic formulas,” 2018, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/36157.