The use of evolutionary programming based on training examples for the generation of finite state machines for controlling objects with complex behavior

DOI10.1134/S1064230713020020zbMath1278.93175OpenAlexW2105016150MaRDI QIDQ393676

S. V. Kazakov, F. N. Tsarev, A. V. Aleksandrov, A. A. Shalyto, Alexey A. Sergushichev

Publication date: 23 January 2014

Published in: Journal of Computer and Systems Sciences International (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1134/s1064230713020020

zbMATH Keywords

evolutionary programminggeneration of finite state machinesloop-the-loop maneuvermodel aircraftobjects with complex behavior

Mathematics Subject Classification ID

Approximation methods and heuristics in mathematical programming (90C59) Application models in control theory (93C95)

Related Items (2)

Modification of the method of generation of control finite-state machines with continuous actions based on training examples ⋮ Inducing finite state machines from training samples using ant colony optimization

Cites Work

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• A genetic algorithm for finding a salesman's route
• Method of reduced tables for generation of automata with a large number of input variables based on genetic programming
• Genetic algorithms: state of the art, problems, and perspectives

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