Sequential Decision-Making in Musical Intelligence, Elad Liebman

Автор: Robert M. Fuhrer; Steven M. Nowick
Название: Sequential Optimization of Asynchronous and Synchronous Finite-State Machines
ISBN: 1461355435 ISBN-13(EAN): 9781461355434
Издательство: Springer
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Цена: 93160.00 T
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Описание: This text contributes to the field of sequential optimization for finite-state machines, introducing several new provably-optimal algorithms, presenting practical software implementations of each of these algorithms and introducing a complete new CAD package, called MINIMALIST.

Автор: Abhijit Ghosh; Srinivas Devadas; A. Richard Newton
Название: Sequential Logic Testing and Verification
ISBN: 1461366224 ISBN-13(EAN): 9781461366225
Издательство: Springer
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Цена: 78350.00 T
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Описание: For instance, in order design reliable inte- gritted circuits, it is necessary to analyze how decisions regarding design rules affect the yield, i.e., the percentage of functional chips obtained by the manufacturing process.

Автор: Jos? Monteiro; Srinivas Devadas
Название: Computer-Aided Design Techniques for Low Power Sequential Logic Circuits
ISBN: 1461379016 ISBN-13(EAN): 9781461379010
Издательство: Springer
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Цена: 139750.00 T
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Описание: Computer-Aided Design Techniques for Low Power Sequential Logic Circuits then presents a survey of methods to optimize logic circuits for low power dissipation which target reduced switching activity.

Автор: Naresh Maheshwari; S. Sapatnekar
Название: Timing Analysis and Optimization of Sequential Circuits
ISBN: 1461375797 ISBN-13(EAN): 9781461375791
Издательство: Springer
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Цена: 93160.00 T
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Автор: Ashar Djaloeis; S. Devadas; A. Richard Newton
Название: Sequential Logic Synthesis
ISBN: 1461366135 ISBN-13(EAN): 9781461366133
Издательство: Springer
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Цена: 93160.00 T
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Описание: 2 Input Encoding Targeting Two-Level Logic . 3 Satisfying Encoding Constraints . 3 Row-Based Constraint Satisfaction . 4 Constraint Satisfaction Using Dichotomies . 3 Heuristics to Minimize the Number of Encoding Bits . 3 Dominance and Disjunctive Relationships to S- isfy Constraints .

Автор: Stephen B. Fountain; Michael D. Bunsey; Joseph H.
Название: Animal Cognition and Sequential Behavior
ISBN: 146135255X ISBN-13(EAN): 9781461352556
Издательство: Springer
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Цена: 139750.00 T
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Автор: Xia Lirong
Название: Learning and Decision-Making from Rank Data
ISBN: 1681734400 ISBN-13(EAN): 9781681734408
Издательство: Mare Nostrum (Eurospan)
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Цена: 61910.00 T
Наличие на складе: Невозможна поставка.
Описание: The ubiquitous challenge of learning and decision-making from rank data arises in situations where intelligent systems collect preference and behavior data from humans, learn from the data, and then use the data to help humans make efficient, effective, and timely decisions. Often, such data are represented by rankings. This book surveys some recent progress toward addressing the challenge from the considerations of statistics, computation, and socio-economics. We will cover classical statistical models for rank data, including random utility models, distance-based models, and mixture models. We will discuss and compare classical and state of-the-art algorithms, such as algorithms based on Minorize-Majorization (MM), Expectation-Maximization (EM), Generalized Method-of-Moments (GMM), rank breaking, and tensor decomposition. We will also introduce principled Bayesian preference elicitation frameworks for collecting rank data. Finally, we will examine socio-economic aspects of statistically desirable decision-making mechanisms, such as Bayesian estimators. This book can be useful in three ways: (1) for theoreticians in statistics and machine learning to better understand the considerations and caveats of learning from rank data, compared to learning from other types of data, especially cardinal data; (2) for practitioners to apply algorithms covered by the book for sampling, learning, and aggregation; and (3) as a textbook for graduate students or advanced undergraduate students to learn about the field. This book requires that the reader has basic knowledge in probability, statistics, and algorithms. Knowledge in social choice would also help but is not required.

Автор: Alena V. Favorskaya; Igor B. Petrov
Название: Innovations in Wave Processes Modelling and Decision Making
ISBN: 3319892894 ISBN-13(EAN): 9783319892894
Издательство: Springer
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Цена: 139750.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book presents methods for full-wave computer simulation that can be used in various applications and contexts, e.g. seismic prospecting, earthquake stability, global seismic patterns on Earth and Mars, medicine, traumatology, ultrasound investigation of the human body, ultrasound and laser operations, ultrasonic non-destructive railway testing, modelling aircraft composites, modelling composite material delamination, etc. The key innovation of this approach is the ability to study spatial dynamical wave processes, which is made possible by cutting-edge numerical finite-difference grid-characteristic methods.The book will benefit all students, researchers, practitioners and professors interested in numerical mathematics, computer science, computer simulation, high-performance computer systems, unstructured meshes, interpolation, seismic prospecting, geophysics, medicine, non-destructive testing and composite materials.

Автор: Marina Resta
Название: Computational Intelligence Paradigms in Economic and Financial Decision Making
ISBN: 3319365258 ISBN-13(EAN): 9783319365251
Издательство: Springer
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Цена: 78350.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The book focuses on a set of cutting-edge research techniques, highlighting the potential of soft computing tools in the analysis of economic and financial phenomena and in providing support for the decision-making process.

Автор: Xia Lirong
Название: Learning and Decision-Making from Rank Data
ISBN: 1681734427 ISBN-13(EAN): 9781681734422
Издательство: Mare Nostrum (Eurospan)
Рейтинг:
Цена: 82230.00 T
Наличие на складе: Невозможна поставка.
Описание: The ubiquitous challenge of learning and decision-making from rank data arises in situations where intelligent systems collect preference and behavior data from humans, learn from the data, and then use the data to help humans make efficient, effective, and timely decisions. Often, such data are represented by rankings. This book surveys some recent progress toward addressing the challenge from the considerations of statistics, computation, and socio-economics. We will cover classical statistical models for rank data, including random utility models, distance-based models, and mixture models. We will discuss and compare classical and state of-the-art algorithms, such as algorithms based on Minorize-Majorization (MM), Expectation-Maximization (EM), Generalized Method-of-Moments (GMM), rank breaking, and tensor decomposition. We will also introduce principled Bayesian preference elicitation frameworks for collecting rank data. Finally, we will examine socio-economic aspects of statistically desirable decision-making mechanisms, such as Bayesian estimators. This book can be useful in three ways: (1) for theoreticians in statistics and machine learning to better understand the considerations and caveats of learning from rank data, compared to learning from other types of data, especially cardinal data; (2) for practitioners to apply algorithms covered by the book for sampling, learning, and aggregation; and (3) as a textbook for graduate students or advanced undergraduate students to learn about the field. This book requires that the reader has basic knowledge in probability, statistics, and algorithms. Knowledge in social choice would also help but is not required.

Автор: Tshilidzi Marwala
Название: Artificial Intelligence Techniques for Rational Decision Making
ISBN: 3319114239 ISBN-13(EAN): 9783319114231
Издательство: Springer
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Цена: 79190.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Artificial Intelligence Techniques for Rational Decision Making

Автор: Ariel Rosenfeld, Sarit Kraus
Название: Predicting Human Decision-Making: From Prediction to Action
ISBN: 1681732742 ISBN-13(EAN): 9781681732749
Издательство: Mare Nostrum (Eurospan)
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Цена: 66530.00 T
Наличие на складе: Невозможна поставка.
Описание: Human decision-making often transcends our formal models of ""rationality."" Designing intelligent agents that interact proficiently with people necessitates the modeling of human behavior and the prediction of their decisions. In this book, we explore the task of automatically predicting human decision-making and its use in designing intelligent human-aware automated computer systems of varying natures—from purely conflicting interaction settings (e.g., security and games) to fully cooperative interaction settings (e.g., autonomous driving and personal robotic assistants). We explore the techniques, algorithms, and empirical methodologies for meeting the challenges that arise from the above tasks and illustrate major benefits from the use of these computational solutions in real-world application domains such as security, negotiations, argumentative interactions, voting systems, autonomous driving, and games. The book presents both the traditional and classical methods as well as the most recent and cutting edge advances, providing the reader with a panorama of the challenges and solutions in predicting human decision-making.