Cycle Based Clustering Using Reversible Cellular Automata

This work proposes cycle based clustering technique using reversible cellular automata (CAs) where ‘closeness’ among objects is represented as objects belonging to the same cycle, that is reachable from each other. The properties of such CAs are exploited for grouping the objects with minimum intra-cluster distance while ensuring that limited number of cycles exist in the configuration-space. The proposed algorithm follows an iterative strategy where the clusters with closely reachable objects of previous level are merged in the present level using an unique auxiliary CA. Finally, it is observed that, our algorithm is at least at par with the best algorithm existing today.