Transactions on Computational Collective Intelligence XXIV

Herausgegeben:Nguyen, Ngoc Thanh; Kowalczyk, Ryszard; Filipe, Joaquim

• Broschiertes Buch

Produktbeschreibung

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 twenty-forth issue contains 9 carefully selected and revised contributions.p>

Produktdetails

• Lecture Notes in Computer Science 9770
• Verlag: Springer / Springer Berlin Heidelberg / Springer, Berlin
• Artikelnr. des Verlages: 978-3-662-53524-0
• 1st ed. 2016
• Seitenzahl: 180
• Erscheinungstermin: 30. September 2016
• Englisch
• Abmessung: 235mm x 155mm x 11mm
• Gewicht: 283g
• ISBN-13: 9783662535240
• ISBN-10: 3662535246
• Artikelnr.: 45611238

Inhaltsangabe

Dynamic Topologies for Particle Swarms.- Evaluative Study of PSO/Snake Hybrid Algorithm and Gradient Path Labeling for Calculating Solar Differential Rotation.- The Uncertainty Quandary: A Study in the Context of the Evolutionary Optimization in Games and other Uncertain Environments.- Hybrid Single Node Genetic Programming for Symbolic Regression.- L2 Designer: A Tool for Genetic L-system Programming in Context of Generative Art.- Manifold Learning Approach toward Constructing State Representation for Robot Motion Generation.- The Existenceof Two Variant Processes in Human Declarative Memory: Evidence Using Machine Learning Classification Techniques in Retrieval Tasks.- Divide and Conquer Ensemble Method for Time Series Forecasting.- Application areas of Ephemeral Computing: A survey.