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Titlebook: Computational Collective Intelligence. Semantic Web, Social Networks and Multiagent Systems; First International Ngoc Thanh Nguyen,Ryszard

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書目名稱Computational Collective Intelligence. Semantic Web, Social Networks and Multiagent Systems
副標(biāo)題First International
編輯Ngoc Thanh Nguyen,Ryszard Kowalczyk,Shyi-Ming Chen
視頻videohttp://file.papertrans.cn/233/232186/232186.mp4
叢書名稱Lecture Notes in Computer Science
圖書封面Titlebook: Computational Collective Intelligence. Semantic Web, Social Networks and Multiagent Systems; First International  Ngoc Thanh Nguyen,Ryszard
描述Computational collective intelligence (CCI) is most often understood as a subfield of artificial intelligence (AI) dealing with soft computing methods that enable group decisions to be made or knowledge to be processed among autonomous units acting in distributed environments. The needs for CCI techniques and tools have grown signi- cantly recently as many information systems work in distributed environments and use distributed resources. Web-based systems, social networks and multi-agent systems very often need these tools for working out consistent knowledge states, resolving conflicts and making decisions. Therefore, CCI is of great importance for today’s and future distributed systems. Methodological, theoretical and practical aspects of computational collective int- ligence, such as group decision making, collective action coordination, and knowledge integration, are considered as the form of intelligence that emerges from the collabo- tion 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. , can support human
出版日期Conference proceedings 2009
關(guān)鍵詞artificial intelligence; collective intelligence; consensus theory; evolutionary computation; fuzzy syst
版次1
doihttps://doi.org/10.1007/978-3-642-04441-0
isbn_softcover978-3-642-04440-3
isbn_ebook978-3-642-04441-0Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightSpringer-Verlag Berlin Heidelberg 2009
The information of publication is updating

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Toward a Self-referential Collective Intelligence Some Philosophical Background of the IEML Researchlar language that provides new methods for semantic interoperability, semantic navigation, collective categorization and self-referential collective intelligence. This research program is compatible with the major standards of the Web of data and is in tune with the current trends in social computin
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A-Teams and Their Applicationsinally to population-based algorithms. Population-based methods have become very popular. They provide good solutions since any constructive method can be used to generate the initial population, and any local search technique can be used to improve each solution in the population. But population-ba
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A Conception for Modification of Learning Scenario in an Intelligent E-learning Systeming path should be suitable for student’s preferences, abilities, interests, learning styles and especially for his current knowledge. Therefore, if a student has a problem with passing a test it is a signal for the system that the offered learning path is not adequate for this user. System should m
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A Token-Based Mutual Exclusion Approach to Improve Collaboration in Distributed Environmentshitecture. This research makes use of a variation of the token-based Naimi-Tréhel’s algorithm by considering only three messages in total as well as reducing the needed information sharing. This ensures to improve the effectiveness of agents’ communication resources and therefore to improve collabor
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