Fuzzy Ant Based Clustering

Various clustering methods based on the behaviour of real ants have been proposed. In this paper, we develop a new algorithm in which the behaviour of the artificial ants is governed by fuzzy IF–THEN rules. Our algorithm is conceptually simple, robust and easy to use due to observed dataset independence of the parameter values involved.

• Type: Conference
• Year: 2004
• Where: ANTSW
• Authors: Steven Schockaert, Martine De Cock, Chris Cornelis, Etienne E. Kerre
• Keywords: ANTSW 2004, Artificial Intelligence, Fuzzy If–then Rules, Observed Dataset Independence, Various Clustering Methods