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Learning Classifier Systems
Learning Classifier Systems (LCS) are a machine learning paradigm introduced by John Holland in 1976. They are rule-based systems in which learning is viewed as a process of ongoing adaptation to a partially unknown environment through genetic algorithms and temporal difference learning. This book provides a unique survey of the current state of the art of LCS and highlights some of the most promising research directions. The first part presents various views of leading people on what learning classifier systems are. The second part is devoted to advanced topics of current interest, including alternative representations, methods for evaluating rule utility, and extensions to existing classifier system models. The final part is dedicated to promising applications in areas like data mining, medical data analysis, economic trading agents, aircraft maneuvering, and autonomous robotics. An appendix comprising 467 entries provides a comprehensive LCS bibliography.
Mechanics for a New Millennium
This volume contains the proceedings of the 2000 International Congress of Theoretical and Applied Mechanics. The book captures a snapshot view of the state of the art in the field of mechanics and will be invaluable to engineers and scientists from a variety of disciplines.
Nonlinear Time Series Analysis
The paradigm of deterministic chaos has influenced thinking in many fields of science. Chaotic systems show rich and surprising mathematical structures. In the applied sciences, deterministic chaos provides a striking explanation for irregular behaviour and anomalies in systems which do not seem to be inherently stochastic. The most direct link between chaos theory and the real world is the analysis of time series from real systems in terms of nonlinear dynamics. Experimental technique and data analysis have seen such dramatic progress that, by now, most fundamental properties of nonlinear dynamical systems have been observed in the laboratory. Great efforts are being made to exploit ideas from chaos theory wherever the data displays more structure than can be captured by traditional methods. Problems of this kind are typical in biology and physiology but also in geophysics, economics, and many other sciences.
Topics in Nonlinear Time Series Analysis
This book provides a thorough review of a class of powerful algorithms for the numerical analysis of complex time series data which were obtained from dynamical systems. These algorithms are based on the concept of state space representations of the underlying dynamics, as introduced by nonlinear dynamics. In particular, current algorithms for state space reconstruction, correlation dimension estimation, testing for determinism and surrogate data testing are presented ? algorithms which have been playing a central role in the investigation of deterministic chaos and related phenomena since 1980. Special emphasis is given to the much-disputed issue whether these algorithms can be successfully employed for the analysis of the human electroencephalogram.
Nonlinear Dynamics and Chaos
Nonlinear dynamics has been successful in explaining complicated phenomena in well-defined low-dimensional systems. Now it is time to focus on real-life problems that are high-dimensional or ill-defined, for example, due to delay, spatial extent, stochasticity, or the limited nature of available data. How can one understand the dynamics of such sys
Dividing the Domestic
In Dividing the Domestic, leading international scholars roll up their sleeves to investigate how culture and country characteristics permeate our households and our private lives. The book introduces novel frameworks for understanding why the household remains a bastion of traditional gender relations—even when employed full-time, women everywhere still do most of the work around the house, and poor women spend more time on housework than affluent women. Education systems, tax codes, labor laws, public polices, and cultural beliefs about motherhood and marriage all make a difference. Any accounting of "who does what" needs to consider the complicity of trade unions, state arrangements for children's schooling, and new cultural prescriptions for a happy marriage. With its cross-national perspective, this pioneering volume speaks not only to sociologists concerned with gender and family, but also to those interested in scholarship on states, public policy, culture, and social inequality.
Seventh IUTAM Symposium on Laminar-Turbulent Transition
The origins of turbulent ?ow and the transition from laminar to turbulent ?ow are the most important unsolved problems of ?uid mechanics and aerodynamics. - sides being a fundamental question of ?uid mechanics, there are numerous app- cations relying on information regarding transition location and the details of the subsequent turbulent ?ow. For example, the control of transition to turbulence is - pecially important in (1) skin-friction reduction of energy ef?cient aircraft, (2) the performance of heat exchangers and diffusers, (3) propulsion requirements for - personic aircraft, and (4) separation control. While considerable progress has been made in the science of laminar to turbulent tr...
Integration for Third Country Nationals in the European Union
This highly original book provides an innovative analysis of EU migration and asylum law and its interplay with equality issues in order to assess the current integration framework for third-country nationals and to explore future scenarios in the European Context. Integration for Third-Country Nationals in the European Union focuses on the nexus between non-discrimination based on nationality and race, and the equality clauses covering different categories of regularly residing third-country nationals within EU law. It highlights the extent to which social rights that have been formally promised to non-EU citizens are enjoyed in practice. The contributing authors Ð who are both academics a...
