Reinforcement learning (RL) and adaptive dynamic programming (ADP) has been one of the most critical research fields in science and engineering for modern complex systems. This book describes the latest RL and ADP tec...
ISBN:
(数字)9781118453988
ISBN:
(纸本)9781118104200
Reinforcement learning (RL) and adaptive dynamic programming (ADP) has been one of the most critical research fields in science and engineering for modern complex systems. This book describes the latest RL and ADP techniques for decision and control in human engineered systems, covering both single player decision and control and multi-player games. Edited by the pioneers of RL and ADP research, the book brings together ideas and methods from many fields and provides an important and timely guidance on controlling a wide variety of systems, such as robots, industrial processes, and economic decision-making.
This is the first book to take a truly comprehensive look at clustering. It begins with an introduction to cluster analysis and goes on to explore: proximity measures; hierarchical clustering; partition clustering; ne...
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ISBN:
(数字)9780470382776
ISBN:
(纸本)9780470276808
This is the first book to take a truly comprehensive look at clustering. It begins with an introduction to cluster analysis and goes on to explore: proximity measures; hierarchical clustering; partition clustering; neural network-based clustering; kernel-based clustering; sequential data clustering; large-scale data clustering; data visualization and high-dimensional data clustering; and cluster validation. The authors assume no previous background in clustering and their generous inclusion of examples and references help make the subject matter comprehensible for readers of varying levels and backgrounds.
Combining biology, computer science, mathematics, and statistics, the field of bioinformatics has become a hot new discipline with profound impacts on all aspects of biology and industrial application. Now, Computatio...
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ISBN:
(数字)9780470199091
ISBN:
(纸本)9780470105269
Combining biology, computer science, mathematics, and statistics, the field of bioinformatics has become a hot new discipline with profound impacts on all aspects of biology and industrial application. Now, computationalintelligence in Bioinformatics offers an introduction to the topic, covering the most relevant and popular CI methods, while also encouraging the implementation of these methods to readers' research.
Introduction to Evolvable Hardware: A Practical Guide for Designing Self-Adaptive Systems provides a fundamental introduction for engineers, designers, and managers involved in the development of adaptive, high reliab...
ISBN:
(数字)9780470049716
ISBN:
(纸本)9780471719779
Introduction to Evolvable Hardware: A Practical Guide for Designing Self-Adaptive Systems provides a fundamental introduction for engineers, designers, and managers involved in the development of adaptive, high reliability systems. It also introduces the concepts of evolvable hardware (EHW) to new researchers in a structured way. With this practical book, you’ll be able to quickly apply the techniques presented to existing design problems.
This Third Edition provides the latest tools and techniques that enable computers to learn The Third Edition of this internationally acclaimed publication provides the latest theory and techniques for using simulated ...
ISBN:
(数字)9780471749219
ISBN:
(纸本)9780471669517
This Third Edition provides the latest tools and techniques that enable computers to learn The Third Edition of this internationally acclaimed publication provides the latest theory and techniques for using simulated evolution to achieve machine intelligence. As a leading advocate for evolutionary computation, the author has successfully challenged the traditional notion of artificial intelligence, which essentially programs human knowledge fact by fact, but does not have the capacity to learn or adapt as evolutionary computation does. Readers gain an understanding of the history of evolutionary computation, which provides a foundation for the author's thorough presentation of the latest theories shaping current research. Balancing theory with practice, the author provides readers with the skills they need to apply evolutionary algorithms that can solve many of today's intransigent problems by adapting to new challenges and learning from experience. Several examples are provided that demonstrate how these evolutionary algorithms learn to solve problems. In particular, the author provides a detailed example of how an algorithm is used to evolve strategies for playing chess and checkers. As readers progress through the publication, they gain an increasing appreciation and understanding of the relationship between learning and intelligence. Readers familiar with the previous editions will discover much new and revised material that brings the publication thoroughly up to date with the latest research, including the latest theories and empirical properties of evolutionary computation. The Third Edition also features new knowledge-building aids. Readers will find a host of new and revised examples. New questions at the end of each chapter enable readers to test their knowledge. Intriguing assignments that prepare readers to manage challenges in industry and research have been added to the end of each chapter as well. This is a must-have reference for professionals in com
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