Computational Intelligence: Collaboration, Fusion and Emergence (Google eBook)
This book is the first in a new series entitled 'Intelligent Systems Reference Library'. It is a collection of chapters written by leading experts, covering a rich and diverse variety of computer-based techniques, all involving some aspect of computational intelligence (CI). Authors in this collection recognize the limitations of individual paradigms, and propose some practical and novel ways in which different CI techniques can be combined with each other, or with more traditional computational techniques, to produce powerful problem-solving environments. Common themes to be found in the various chapters of this collection include the following: Fusion, Collaboration, and Emergence.
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Part II Fusing Evolutionary Algorithms and Fuzzy Logic
Part III Adaptive Solution Schemes
Part IV MultiAgent Systems
Part V Computer Vision
Part VI Communications for CI Systems
accuracy adaptive agent-based applications approach Artiﬁcial Intelligence behavior beneﬁt best response cells chapter classiﬁer cluster coefﬁcient collaboration complexity Computational Intelligence constraints cooperation crowd data set DC DC DC deﬁned deﬁnition distributed domain dynamic efﬁcient engineering ensemble environment Equation estimation evaluation evolutionary algorithms Evolutionary Computation example FClust ﬁeld ﬁnancial ﬁnd ﬁnding ﬁnite ﬁrst ﬁtness ﬁxed function fuzzy logic fuzzy rule-based classiﬁers fuzzy rule-based systems fuzzy rules fuzzy sets fuzzy systems genetic algorithms genetic fuzzy systems Genetic Programming Heidelberg heuristics human hybrid identiﬁcation IEEE Trans immune system individual input interactions iterations LNCS machine learning measure mechanism methods multi-agent system multiobjective optimization negotiation neural networks nodes observed optimization output parameters Pareto partition patterns peptides performance population prediction problem proposed protein rule selection sensor signiﬁcant simulation software agents solving speciﬁc Springer strategies structure techniques tion training data values variables vector