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Sudoku puzzles are logical number placement puzzle games. They are classified as combinatorial optimization problems and are NP-complete. To solve problems in this complexity class, metaheuristic approaches, such as genetic algorithms (GAs), are often adopted. However, conventional GAs with random swap mutations suffer from slow convergence, especially in extremely difficult sudoku puzzles, in which...
The pursuit problem is a conventional benchmark in distributed artificial intelligence research. The focal point of previous work in this domain has been the development of coordination mechanisms for predators that cooperatively hunt prey in a typically discrete grid world. This paper investigates a pursuit problem in a continuous torus field on the basis of swarm robotics. Twenty predator robots...
A hybrid evolutionary algorithm based on (μ, λ) evolutionary algorithms and particle swarm optimization is proposed for the numerical optimization problems. In order to find out the performance of the hybrid, the computer experiment is tested on dinosaur's gait generation problem. Experimental results show that hybrid optimization finds maximum fitness and is faster in the first phase.
Artificial bee colony (ABC) algorithm is one of the most recently introduced swarm intelligence based algorithm which foraging the behavior of honey bee colonies. In order to improve the convergence performance and searching speed of finding best solution, self adaptive hybrid ABC (SAHABC) is proposed in this paper. For evaluating the performance of standard ABC and proposed SAHABC algorithms, we...
Swarm robotics is the research field of multi-robot systems which consist of many homogeneous autonomous robots without any type of global controllers. In this paper, an evolutionary robotics approach, i.e., the method that the robot controllers are designed by evolutionary algorithms with artificial neural networks, is applied. And we apply an incremental approach to evolution within the context...
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