Описание: This book is a collection of papers contributed by some of the greatest names in the areas of chaos and nonlinear dynamics. Each paper examines a research topic at the frontier of the area of dynamical systems. As well as reviewing recent results, each paper also discusses the future perspectives of each topic. The result is an invaluable snapshot of the state of the ?eld by some of the most important researchers in the area. The ?rst contribution in this book (the section entitled "How did you get into Chaos?") is actually not a paper, but a collection of personal accounts by a number of participants of the conference held in Aberdeen in September 2007 to honour Celso Grebogi's 60th birthday. At the instigation of James Yorke, many of the most well-known scientists in the area agreed to share their tales on how they got involved in chaos during a celebratory dinner in Celso's honour during the conference. This was recorded in video, we felt that these accounts were a valuable historic document for the ?eld. So we decided to transcribe it and include it here as the ?rst section of the book.
Описание: Knowledge processing and decision making in agent-based systems constitute the key components of intelligent machines. This book contains the latest research in the area of knowledge processing and decision making in agent-based systems.
Автор: Pierre Bessi?re; Christian Laugier; Roland Siegwar Название: Probabilistic Reasoning and Decision Making in Sensory-Motor Systems ISBN: 3642097847 ISBN-13(EAN): 9783642097843 Издательство: Springer Рейтинг: Цена: 26120.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The chapters contain a sizable segment of cognitive systems research in Europe. Contributions come from leading academic institutions within the European projects Bayesian Inspired Brain and Artifact (BIBA) and Bayesian Approach to Cognitive Systems (BACS).
Автор: Mangkusubroto Название: Systems Science for Complex Policy Making ISBN: 4431552723 ISBN-13(EAN): 9784431552727 Издательство: Springer Рейтинг: Цена: 11179.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This volume applies a systems science perspective to complex policy making dynamics, using the case of Indonesia to illustrate the concepts. Indonesia is an archipelago with a high heterogeneity. Her people consist of 1,340 tribes who are scattered over 17,508 islands. Every region has different natural strengths and conditions. In the national development process all regions depend on one another other while optimizing their own conditions. In addition to this diversity, Indonesia also employs a democratic system of government with high regional autonomy. A democratic government puts a high value on individual freedom, but on the other hand, conflicts of interest also occur frequently. High regional autonomy also often causes problems in coordination among agencies and regional governments. This uniqueness creates a kind of complexity that is rarely found in other countries.These daily complexities requires intensive interaction, negotiation processes, and coordination. Such necessities should be considered in public policy making and in managing the implementation of national development programs. In this context, common theories and best practices generated on the basis of more simplified assumptions often fail. Systems science offer a way of thinking that can take into account and potentially overcome these complexities. However, efforts to apply systems science massively and continuously in real policy making by involving many stakeholders are still rarely carried out. The first part of the book discusses the gap between the existing public policy-making approach and needs in the real world. After that, the characteristics of the appropriate policy-making process in a complex environment and how this process can be carried are described. In later sections, important systems science concepts that can be applied in managing these complexities are discussed. Finally, the efforts to apply these concepts in real cases in Indonesia are described.
Автор: Aleksandar Zecevic; Dragoslav D. Siljak Название: Control of Complex Systems ISBN: 1441912150 ISBN-13(EAN): 9781441912152 Издательство: Springer Рейтинг: Цена: 19564.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Decompositions of Large-Scale Systems.- Information Structure Constraints.- Algebraic Constraints on the Gain Matrix.- Regions of Attraction.- Parametric Stability.- Future Directions: Dynamic Graphs.
Автор: John Seiffertt; Donald C. Wunsch Название: Unified Computational Intelligence for Complex Systems ISBN: 364226395X ISBN-13(EAN): 9783642263958 Издательство: Springer Рейтинг: Цена: 20962.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This is the first book to present a computational intelligence architecture capable of learning in unsupervised, supervised, or reinforcement learning modes. It is also the first to cover applications of time scales mathematics to engineering applications.
Автор: Van-Nam Huynh; Masahiro Inuiguchi; Bac Le; Nguyen Название: Integrated Uncertainty in Knowledge Modelling and Decision Making ISBN: 3319490451 ISBN-13(EAN): 9783319490458 Издательство: Springer Рейтинг: Цена: 12578.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book constitutes the refereed proceedings of the 5th International Symposium on Integrated Uncertainty in Knowledge Modelling and Decision Making, IUKM 2016, held in Da Nang, Vietnam, in November/December 2016.
The IUKM symposia aim to provide a forum for exchanges of research results and ideas, and experience of application among researchers and practitioners involved with all aspects of uncertainty modelling and management.
Автор: Rouse William B Название: Modeling and Visualization of Complex Systems and Enterprise ISBN: 1118954130 ISBN-13(EAN): 9781118954133 Издательство: Wiley Рейтинг: Цена: 16466.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Explains multi-level models of enterprise systems and covers modeling methodology This book addresses the essential phenomena underlying the overall behaviors of complex systems and enterprises. Understanding these phenomena can enable improving these systems.
Causality has been a subject of study for a long time. Often causality is confused with correlation. Human intuition has evolved such that it has learned to identify causality through correlation. In this book, four main themes are considered and these are causality, correlation, artificial intelligence and decision making. A correlation machine is defined and built using multi-layer perceptron network, principal component analysis, Gaussian Mixture models, genetic algorithms, expectation maximization technique, simulated annealing and particle swarm optimization. Furthermore, a causal machine is defined and built using multi-layer perceptron, radial basis function, Bayesian statistics and Hybrid Monte Carlo methods. Both these machines are used to build a Granger non-linear causality model. In addition, the Neyman-Rubin, Pearl and Granger causal models are studied and are unified. The automatic relevance determination is also applied to extend Granger causality framework to the non-linear domain. The concept of rational decision making is studied, and the theory of flexibly-bounded rationality is used to extend the theory of bounded rationality within the principle of the indivisibility of rationality. The theory of the marginalization of irrationality for decision making is also introduced to deal with satisficing within irrational conditions. The methods proposed are applied in biomedical engineering, condition monitoring and for modelling interstate conflict.
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