A hybrid Q-learning sine-cosine-based strategy for addressing the combinatorial test suite minimization problem

The sine-cosine algorithm (SCA) is a new population-based meta-heuristic algorithm. In addition to exploiting sine and cosine functions to perform local and global searches (hence the name sine-cosine), the SCA introduces several random and adaptive parameters to facilitate the search process. Altho...

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Veröffentlicht in:	PloS one 2018-05, Vol.13 (5), p.e0195675-e0195675
Hauptverfasser:	Zamli, Kamal Z, Din, Fakhrud, Ahmed, Bestoun S, Bures, Miroslav
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Artificial intelligence Biology and Life Sciences Combinatorial analysis Computer and Information Sciences Computer engineering Computer Science Confidence intervals Cybernetics Datavetenskap Electrical engineering Genetic algorithms Heuristic Heuristic methods Jumping Learning Machine learning Maxima Medicine and Health Sciences Minima Optimization Particle swarm optimization Physical Sciences Reinforcement Reinforcement learning (Machine learning) Research and Analysis Methods Search process Size reduction Software engineering Statistical analysis Strategy Swarm intelligence Trigonometric functions
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