We apply an adapted version of Particle Swarm Optimization to distributed unsupervised robotic learning in groups of robots with only local information. The performance of the lea...
One of the most critical issues that remains to be fully addressed in existing multimodal evolutionary algorithms is the difficulty in pre-specifying parameters used for estimatin...
Simplified forms of the particle swarm algorithm are very beneficial in contributing to understanding of what makes a PSO swarm function in the way that it does. One of these form...
Extracting natural groups of the unlabeled data is known as clustering. To improve the stability and robustness of the clustering outputs, clustering ensembles have emerged recent...
Niching is an important technique for multimodal optimization. Most existing niching methods require specification of certain niching parameters in order to perform well. These nic...