These Transactions publish research in computer-based methods of computational collective intelligence (CCI) and their applications in a wide range of fields such as the Semantic Web, social networks and multi-agent systems. TCCI strives to cover new methodological, theoretical and practical aspects of CCI understood as the form of intelligence that emerges from the collaboration and competition of many individuals (artificial and/or natural). The application of multiple computational intelligence technologies such as fuzzy systems, evolutionary computation, neural systems, consensus theory, etc., aims to support human and other collective intelligence and to create new forms of CCI in natural and/or artificial systems. This fourth issue contains a collection of 6 articles selected from high-quality submissions. The first paper of Ireneusz Czarnowski entitled "Distributed Learning with Data Reduction" consists of 120 pages and has a monograph character. The second part consists of five regular papers addressing advances in the foundations and applications of computational collective intelligence.
"synopsis" may belong to another edition of this title.
These Transactions publish research in computer-based methods of computational collective intelligence (CCI) and their applications in a wide range of fields such as the Semantic Web, social networks and multi-agent systems. TCCI strives to cover new methodological, theoretical and practical aspects of CCI understood
as the form of intelligence that emerges from the collaboration and competition of many individuals (artificial and/or natural). The application of multiple computational intelligence technologies such as fuzzy systems, evolutionary computation, neural systems, consensus theory, etc., aims to support human and other collective intelligence and to create new forms of CCI in natural and/or artificial systems.
This fourth issue contains a collection of 6 articles selected from high-quality submissions. The first paper of Ireneusz Czarnowski entitled "Distributed Learning with Data Reduction" consists of 120 pages and has a monograph chracter. The second part consists of five regular papers adressing advances in the foundations and applications of computational collective intelligence.
"About this title" may belong to another edition of this title.
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