標題: Titlebook: Computational Intelligence; Collaboration, Fusio Christine L. Mumford,Lakhmi C. Jain Book 2009 Springer-Verlag Berlin Heidelberg 2009 Multi [打印本頁] 作者: 宣告無效 時間: 2025-3-21 19:22
書目名稱Computational Intelligence影響因子(影響力)
書目名稱Computational Intelligence影響因子(影響力)學科排名
書目名稱Computational Intelligence網(wǎng)絡公開度
書目名稱Computational Intelligence網(wǎng)絡公開度學科排名
書目名稱Computational Intelligence被引頻次
書目名稱Computational Intelligence被引頻次學科排名
書目名稱Computational Intelligence年度引用
書目名稱Computational Intelligence年度引用學科排名
書目名稱Computational Intelligence讀者反饋
書目名稱Computational Intelligence讀者反饋學科排名
作者: Defraud 時間: 2025-3-21 20:45 作者: 朦朧 時間: 2025-3-22 04:11 作者: 沐浴 時間: 2025-3-22 07:49 作者: 單挑 時間: 2025-3-22 11:06 作者: encyclopedia 時間: 2025-3-22 14:37 作者: encyclopedia 時間: 2025-3-22 19:39
M. H. A. Davis,Steven I. Marcustics in order to solve hard computational search problems. An extension of the original hyper-heuristic idea is to generate new heuristics which are not currently known. These approaches operate on a search space of heuristics rather than directly on a search space of solutions to the underlying pro作者: Hyperlipidemia 時間: 2025-3-23 01:10 作者: 錯事 時間: 2025-3-23 03:52 作者: oncologist 時間: 2025-3-23 07:43
https://doi.org/10.1007/978-3-031-54071-4ion, and autonomy of design agents has been recognized as the main contributor to novelty and innovation of solutions. Unfortunately, agents’ autonomy can make the design environment chaotic and inefficient. To address this dilemma of distributed versus central control in complex system design, deci作者: hematuria 時間: 2025-3-23 10:15
https://doi.org/10.1007/978-3-031-54071-4 As work in these fields develops, such systems face increasing challenges. Two particular challenges are decision making in uncertain and partially-observable environments, and coordination with other agents in such environments. Although uncertainty and coordination have been tackled as separate p作者: 摸索 時間: 2025-3-23 15:15
An Introduction to Stochastic Game Theoryd) agents. In this context we discuss both dynamic team formation among the former, as well as partner selection strategies with the latter type of agent. One-shot, long-term, and (fuzzy-based) flexible formation strategies are compared and contrasted, and experiments described which compare these s作者: 消息靈通 時間: 2025-3-23 19:02 作者: 細查 時間: 2025-3-24 01:40
Shane M. Haas,Jeffrey H. Shapirodes computer vision has become increasingly interested in studying crowds and their dynamics: because the phenomenon is of great scientific interest, it offers new computational challenges and because of a rapid increase in video surveillance technology deployed in public and private spaces. In this作者: 注視 時間: 2025-3-24 04:02 作者: Astigmatism 時間: 2025-3-24 07:46 作者: 雕鏤 時間: 2025-3-24 11:51
Computational Intelligence978-3-642-01799-5Series ISSN 1868-4394 Series E-ISSN 1868-4408 作者: 粗語 時間: 2025-3-24 17:50
Entropy, Information and Energy FlowsThis chapter introduces the book. It begins with a historical perspective on Computational Intelligence (CI), and discusses its relationshipwith the longer established term “Artificial Intelligence” (AI). The chapter then gives a brief overview of the main CI techniques, and concludes with short summaries of all the chapters in the book.作者: 征服 時間: 2025-3-24 19:22
Synergy in Computational IntelligenceThis chapter introduces the book. It begins with a historical perspective on Computational Intelligence (CI), and discusses its relationshipwith the longer established term “Artificial Intelligence” (AI). The chapter then gives a brief overview of the main CI techniques, and concludes with short summaries of all the chapters in the book.作者: 安心地散步 時間: 2025-3-25 01:02
Computational Intelligence: The Legacy of Alan Turing and John von Neumannf Alan Turing and John von Neumann. For Turing the creation of machines with human-like intelligence was only a question of programming time. In his research he identified the most relevant problems concerning evolutionary computation, learning, and structure of an artificial brain. Many problems ar作者: WAIL 時間: 2025-3-25 05:07 作者: 小平面 時間: 2025-3-25 10:56 作者: FLOUR 時間: 2025-3-25 14:04 作者: 補助 時間: 2025-3-25 17:32 作者: 羊欄 時間: 2025-3-25 20:22 作者: Minuet 時間: 2025-3-26 00:47
Collaborative Computational Intelligence in Economics the collaboration within the realm of computational intelligence, and, second, the collaboration beyond the realm of it. These two forms of collaboration have had a significant impact upon the current state of economics. First, they enhance and enrich the heterogeneous-agent research paradigm in ec作者: Pulmonary-Veins 時間: 2025-3-26 04:49
IMMUNE: A Collaborating Environment for Complex System Designion, and autonomy of design agents has been recognized as the main contributor to novelty and innovation of solutions. Unfortunately, agents’ autonomy can make the design environment chaotic and inefficient. To address this dilemma of distributed versus central control in complex system design, deci作者: 吞吞吐吐 時間: 2025-3-26 12:11
Bayesian Learning for Cooperation in Multi-Agent Systems As work in these fields develops, such systems face increasing challenges. Two particular challenges are decision making in uncertain and partially-observable environments, and coordination with other agents in such environments. Although uncertainty and coordination have been tackled as separate p作者: Lumbar-Spine 時間: 2025-3-26 14:32 作者: semble 時間: 2025-3-26 19:57
Predicting Trait Impressions of Faces Using Classifier Ensemblesial morphology. Exploring machine models of people’s impressions of faces has value in the fields of social psychology and human-computer interaction. Our first concern in designing this study was developing a sound ground truth for this problem domain. We accomplished this by collecting a large num作者: 儀式 時間: 2025-3-26 23:49
The Analysis of Crowd Dynamics: From Observations to Modellingdes computer vision has become increasingly interested in studying crowds and their dynamics: because the phenomenon is of great scientific interest, it offers new computational challenges and because of a rapid increase in video surveillance technology deployed in public and private spaces. In this作者: Terminal 時間: 2025-3-27 02:45 作者: nauseate 時間: 2025-3-27 07:14 作者: 感激小女 時間: 2025-3-27 11:00
Michiel Hazewinkel,Jan C. Willemscomplexity tradeoff surface in some studies. These studies are often referred to as multiobjective genetic fuzzy systems. In this chapter, we first briefly explain the concept of accuracy-complexity tradeoff in the design of fuzzy rule-based systems. Next we explain various studies in multiobjective作者: 單純 時間: 2025-3-27 13:53
M. H. A. Davis,Steven I. Marcusing is the most widely used methodology. A detailed discussion is presented including the steps needed to apply this technique, some representative case studies, a literature review of related work, and a discussion of relevant issues. Our aim is to convey the exciting potential of this innovative a作者: 角斗士 時間: 2025-3-27 20:46
https://doi.org/10.1007/978-3-031-54071-4onomous collaborations is sensed and monitored by a central unit. The collaboration complexity, which is the collective problem solving capability of the design system, is compared to the complexity of the problem estimated from simulation based techniques. In this regard IMMUNE is an artificial imm作者: negotiable 時間: 2025-3-27 23:54
Arthur C. Heinricher,Richard H. Stockbridgeds employing ensembles are as capable as most individual human beings are in their ability to predict the social impressions certain faces make on the average human observer. Single classifier systems did not match human performance as well as the ensembles did. Included in this chapter is a tutoria作者: Chauvinistic 時間: 2025-3-28 02:11 作者: 細查 時間: 2025-3-28 07:19 作者: 青春期 時間: 2025-3-28 13:49 作者: concert 時間: 2025-3-28 17:36
Multiobjective Genetic Fuzzy Systemscomplexity tradeoff surface in some studies. These studies are often referred to as multiobjective genetic fuzzy systems. In this chapter, we first briefly explain the concept of accuracy-complexity tradeoff in the design of fuzzy rule-based systems. Next we explain various studies in multiobjective作者: Tidious 時間: 2025-3-28 19:05 作者: landmark 時間: 2025-3-29 02:02
IMMUNE: A Collaborating Environment for Complex System Designonomous collaborations is sensed and monitored by a central unit. The collaboration complexity, which is the collective problem solving capability of the design system, is compared to the complexity of the problem estimated from simulation based techniques. In this regard IMMUNE is an artificial imm作者: scrutiny 時間: 2025-3-29 06:04
Predicting Trait Impressions of Faces Using Classifier Ensemblesds employing ensembles are as capable as most individual human beings are in their ability to predict the social impressions certain faces make on the average human observer. Single classifier systems did not match human performance as well as the ensembles did. Included in this chapter is a tutoria作者: Mortar 時間: 2025-3-29 08:40
1868-4394 s precise de?nition. Some practitioners limit its scope to schemes involving evolutionary algorithms, neural networks, fuzzy logic, or hybrids of these. For others, the de?nition is a little more ?exible, and will include paradigms such as Bayesian 978-3-642-24262-5978-3-642-01799-5Series ISSN 1868-4394 Series E-ISSN 1868-4408 作者: 技術 時間: 2025-3-29 11:56
Shane M. Haas,Jeffrey H. Shapiroynamics. The problem is studied to offer methods to measure crowd dynamics and model the complex movements of a crowd. The refined matching of local descriptors is used to measure crowd motion and statistical analysis and a kind of neural network, self-organizing maps were employed to learn crowd dynamics models.作者: 轉向 時間: 2025-3-29 16:29 作者: CRP743 時間: 2025-3-29 20:46
1868-4394 gence (CI). It is a c- lection of chapters that covers a rich and diverse variety of computer-based techniques, all involving some aspect of computational intelligence, but each one taking a somewhat pragmatic view. Many complex problems in the real world require the application of some form of what作者: Chronic 時間: 2025-3-30 01:15
Book 2009 techniques, all involving some aspect of computational intelligence, but each one taking a somewhat pragmatic view. Many complex problems in the real world require the application of some form of what we loosely call “intel- gence”fortheirsolution. Fewcanbesolvedbythenaiveapplicationofasingle techn作者: anticipate 時間: 2025-3-30 07:55
Stochastic Models of Computer Networksrd problem instances. Our algorithm shows how the speed of more na?ve algorithms can be utilised safe in the knowledge that the exceptional behaviour can be bounded. Our work clearly demonstrates the potential benefits of the adaptive approach and opens a new front of research for the constraint satisfaction community.作者: 刪除 時間: 2025-3-30 09:29
https://doi.org/10.1007/BFb0120739 hot current trends and prospects. In essence, we paint a complete picture of these two lines of research with the aim of showing the benefits derived from the synergy between evolutionary algorithms and fuzzy logic.作者: 服從 時間: 2025-3-30 15:49
Michiel Hazewinkel,Jan C. Willems, various hybridizations of the CI tools facilitate the development of more comprehensive treatments of the economic and financial uncertainties in terms of both their quantitative and qualitative aspects.作者: 滔滔不絕地說 時間: 2025-3-30 18:29
