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College Algebra
College Algebra

The Barnett/Ziegler/Byleen/Sobecki College Algebra series is designed to give students a solid grounding in pre-calculus topics in a user-friendly manner. The series emphasizes computational skills, ideas, and problem solving rather than theory. Explore/Discuss boxes integrated throughout each text encourage students to think critically about...

Modeling and Reasoning with Bayesian Networks
Modeling and Reasoning with Bayesian Networks

Bayesian networks have received a lot of attention over the last few decades from both scientists and engineers, and across a number of fields, including artificial intelligence (AI), statistics, cognitive science, and philosophy.

Perhaps the largest impact that Bayesian networks have had is on the field of AI, where they were...

Handbook of Multisensor Data Fusion: Theory and Practice, Second Edition (Electrical Engineering and Applied Signal Processing)
Handbook of Multisensor Data Fusion: Theory and Practice, Second Edition (Electrical Engineering and Applied Signal Processing)
In the years since the bestselling first edition, fusion research and applications have adapted to service-oriented architectures and pushed the boundaries of situational modeling in human behavior, expanding into fields such as chemical and biological sensing, crisis management, and intelligent buildings.

Handbook of Multisensor Data...

Probabilistic Graphical Models: Principles and Techniques (Adaptive Computation and Machine Learning series)
Probabilistic Graphical Models: Principles and Techniques (Adaptive Computation and Machine Learning series)

Most tasks require a person or an automated system to reason--to reach conclusions based on available information. The framework of probabilistic graphical models, presented in this book, provides a general approach for this task. The approach is model-based, allowing interpretable models to be constructed and then manipulated by reasoning...

How We Cooperate: A Theory of Kantian Optimization
How We Cooperate: A Theory of Kantian Optimization
A new theory of how and why we cooperate, drawing from economics, political theory, and philosophy to challenge the conventional wisdom of game theory

Game theory explains competitive behavior by working from the premise that people are self-interested. People don’t just compete, however; they also
...
Bayesian Reasoning and Machine Learning
Bayesian Reasoning and Machine Learning
We live in a world that is rich in data, ever increasing in scale. This data comes from many di erent sources in science (bioinformatics, astronomy, physics, environmental monitoring) and commerce (customer databases, nancial transactions, engine monitoring, speech recognition, surveillance, search). Possessing the knowledge as to...
Discovering Geometry: An Investigative Approach
Discovering Geometry: An Investigative Approach
Discovering Geometry is designed so that you can be actively engaged as you learn geometry. In this book you "learn by doing." You will leam to use the tools of geometry and to perform geometry investigations with them. Many of the investigations are carried out in small cooperative groups in which you jointly plan...
Calculus
Calculus

The new edition calculus textbook has been thoroughly revised. It continues to embrace the best aspects of reform by combining the traditional theoretical aspects of calculus with creative teaching and learning techniques. This is accomplished by a focus on conceptual understanding, the use of real-world data and real-life applications,...

Introduction to Statistical Relational Learning (Adaptive Computation and Machine Learning)
Introduction to Statistical Relational Learning (Adaptive Computation and Machine Learning)
Handling inherent uncertainty and exploiting compositional structure are fundamental to understanding and designing large-scale systems. Statistical relational learning builds on ideas from probability theory and statistics to address uncertainty while incorporating tools from logic, databases, and programming languages to represent structure. In...
Foundations of Neural Networks, Fuzzy Systems, and Knowledge Engineering
Foundations of Neural Networks, Fuzzy Systems, and Knowledge Engineering
Here we have a comprehensive, problem-oriented, engineering perspective on the uses of neural nets, fuzzy systems, and hybrids that emphasizes practical solutions to everyday artificial intelligence (AI) problems over abstract theoretical noodling. Intended for upper-division students and postgraduates who need a...
Argumentation Methods for Artificial Intelligence in Law
Argumentation Methods for Artificial Intelligence in Law
"In this book, Walton presents his perspective on argumentation methods for artificial intelligence and law. … the different tools are combined in a way that makes them potentially useful for understanding legal reasoning. … this book offers a valuable perspective on the current state and future research directions of...
Predictive Maintenance in Dynamic Systems: Advanced Methods, Decision Support Tools and Real-World Applications
Predictive Maintenance in Dynamic Systems: Advanced Methods, Decision Support Tools and Real-World Applications
This book provides a complete picture of several decision support tools for predictive maintenance. These include embedding early anomaly/fault detection, diagnosis and reasoning, remaining useful life prediction (fault prognostics), quality prediction and self-reaction, as well as optimization, control and self-healing techniques. It shows...
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