Buzhinsky, I. P.; Ulyantsev, V. I.; Chivilikhin, D. S.; Shalyto, A. A. Inducing finite state machines from training samples using ant colony optimization. (English. Russian original) Zbl 1308.93165 J. Comput. Syst. Sci. Int. 53, No. 2, 256-266 (2014); translation from Izv. Ross. Akad. Nauk, Teor. Sist. Upr. 2014, No. 2, 111-121 (2014). Summary: A method for control finite state machine (FSM) induction in which an ant colony optimization algorithm is used for search optimization is proposed. The efficiency of this method is estimated using the generation of FSMs for controlling a model of an unmanned aerial vehicle (UAV). It is shown that the proposed method outperforms the method based on genetic algorithms both in terms of performance and quality. Cited in 2 Documents MSC: 93C95 Application models in control theory 93C85 Automated systems (robots, etc.) in control theory 93A14 Decentralized systems Software:FlightGear PDFBibTeX XMLCite \textit{I. P. Buzhinsky} et al., J. Comput. Syst. Sci. Int. 53, No. 2, 256--266 (2014; Zbl 1308.93165); translation from Izv. Ross. Akad. Nauk, Teor. Sist. Upr. 2014, No. 2, 111--121 (2014) Full Text: DOI References: [1] N. I. Polikarpova and A. A. Shalyto, Automata-Based Programming (Piter, St. Petersburg, 1991) [in Russian], http://is.ifmo.ru/books/-book.pdf · Zbl 1308.68073 [2] Kleban, V. O.; Shalyto, A. A., Development of control system for a small-size helicopter, 12-16 (2011) [3] F. N. Tsarev and A. A. Shalyto, “The use of genetic programming for generating a finite state machine in the smart ant problem,” in Proc. of the 4th Int. Conf. on Integrated Models and Soft Computations in Artificial Intelligence (Fizmatlit, Moscow, 2007), pp. 590-597. http://is.ifmo.ru/genalg/-ant-ga.pdf · Zbl 1077.90561 [4] Tsarev, F. N., Combined use of genetic programming, finite state machines, and artificial neural networks for designing a control system for an unmanned aerial vehicle, 12-16 (2011) [5] L. A. Gladkov, V. V. Kureichik, and V. M. Kureichik, Genetic Algorithms (Fizmatlit, Moscow, 2006) [in Russian]. · Zbl 1260.90142 [6] S. Russell and P. Norvig, Artificial Intelligence: A Modern Approach (Prentice Hall, Upper Saddle River, N.J., 2003; Vil’yams, Moscow, 2003). · Zbl 0835.68093 [7] J. R. Koza, Genetic Programming: On the Programming of Computers by Means of Natural Selection (MIT Press, Cambridge, (1992). · Zbl 0850.68161 [8] V. M. Kureichik, “Genetic Algorithms: State of the Art, Problems, and Perspectives,” J. Comput. Syst. Sci. Int. 38, 137-152 (1999). · Zbl 1077.90561 [9] V. M. Kureichik and S. I. Rodzin, “Evolutionary Algorithms: Genetic Programming,” J. Comput. Syst. Sci. Int. 41, 123-132 (2002). [10] Heule, M.; Verwer, S., Exact DFA identification using SAT solvers, No. 6339, 66-79 (2012) · Zbl 1291.68192 · doi:10.1007/978-3-642-15488-1_7 [11] V. Ulyantsev and F. Tsarev, “Extended finite-state machine induction using SAT-solver,” in Proc. of the 14th IFAC Symp. on Information Control Problems in Manufacturing (INCOM’12), 2012, pp. 512-517. [12] T. H. Cormen, C. E. Leiserson, and R. L. Rivest, Introduction to Algorithms (MIT Press, Cambridge, Mass., 1990; Vil’yams, Moscow, 1999). · Zbl 1158.68538 [13] N. I. Polikarpova, V. N. Tochilin, and A. A. Shalyto, “Method of reduced tables for generation of automata with a large number of input variables based on genetic programming,” J. Comput. Syst. Sci. Int. 49, 265-282 (2010). · Zbl 1308.68073 · doi:10.1134/S1064230710020127 [14] A. V. Aleksandrov, S. V. Kazakov, A. A. Sergushichev, F. N. Tsarev, and A. A. Shalyto, “The use of evolutionary programming based on training examples for the generation of finite state machines for controlling objects with complex behavior,” J. Comput. Syst. Sci. Int. 52, 410-425 (2013). · Zbl 1278.93175 · doi:10.1134/S1064230713020020 [15] M. Dorigo, “Optimization, learning and natural algorithms,” PhD Thesis (Dipartimento di Elettronica, Politechnico di Milano, Milano, 1992). [16] M. Dorigo and T. Stützle, Ant Colony Optimization (MIT Press, Cambridge, Mass., 2004). · Zbl 1092.90066 · doi:10.1007/b99492 [17] D. Chivilikhin and V. Ulyantsev, “Learning finite-state machines with ant colony optimization,” Lect. Notes Comput. Sci. 7461, 268-275 (2012). · doi:10.1007/978-3-642-32650-9_27 [18] FlightGear. http://www.flightgear.org/. Accessed February 14, 2013. This reference list is based on information provided by the publisher or from digital mathematics libraries. Its items are heuristically matched to zbMATH identifiers and may contain data conversion errors. In some cases that data have been complemented/enhanced by data from zbMATH Open. This attempts to reflect the references listed in the original paper as accurately as possible without claiming completeness or a perfect matching.