The STUDIA UNIVERSITATIS BABEŞ-BOLYAI issue article summary

The summary of the selected article appears at the bottom of the page. In order to get back to the contents of the issue this article belongs to you have to access the link from the title. In order to see all the articles of the archive which have as author/co-author one of the authors mentioned below, you have to access the link from the author's name.

The density classification problem is a prototypical distributed computational task for Cellular Automata widely studied for the analysis of complex systems. This paper focuses on evolutionary models designed to approach this problem, particularly on the importance of search operators in the context of evolutionary algorithms. Different collaborative re- combination operators are described and engaged in an evolutionary search framework for the density classification task in cellular automata. The significance of considering genetic material from parents, global best/worst solutions and the individual’s best ancestors in the recombination process is discussed.

Key words and phrases. evolutionary algorithms, density classification task, cellular automata, collaborative search.