Algorithms for Decision Making
| Price | $95.00
|
| eBook | Free |
| Rating |  |
| Authors | Mykel J. Kochenderfer, Tim A. Wheeler, Kyle H. Wray |
| Publisher | Self-publishing |
| Published | 2022 |
| Pages | 700 |
| Language | English |
| Format | Paper book / ebook (PDF) |
| ISBN-10 | 0262047012 |
| ISBN-13 | 9780262047012 |
A broad introduction to algorithms for decision making under uncertainty, introducing the underlying mathematical problem formulations and the algorithms for solving them.
Automated decision-making systems or decision-support systems - used in applications that range from aircraft collision avoidance to breast cancer screening - must be designed to account for various sources of uncertainty while carefully balancing multiple objectives. This textbook provides a broad introduction to algorithms for decision making under uncertainty, covering the underlying mathematical problem formulations and the algorithms for solving them.
The book first addresses the problem of reasoning about uncertainty and objectives in simple decisions at a single point in time, and then turns to sequential decision problems in stochastic environments where the outcomes of our actions are uncertain. It goes on to address model uncertainty, when we do not start with a known model and must learn how to act through interaction with the environment; state uncertainty, in which we do not know the current state of the environment due to imperfect perceptual information; and decision contexts involving multiple agents. The book focuses primarily on planning and reinforcement learning, although some of the techniques presented draw on elements of supervised learning and optimization. Algorithms are implemented in the Julia programming language. Figures, examples, and exercises convey the intuition behind the various approaches presented.
- Mykel J. Kochenderfer
- Tim A. Wheeler
- Kyle H. Wray
5 5 6
Similar Books
Reinforcement and Systemic Machine Learning for Decision Making 
by Parag Kulkarni
There are always difficulties in making machines that learn from experience. Complete information is not always available - or it becomes available in bits and pieces over a period of time. With respect to systemic learning, there is a need to understand the impact of decisions and actions on a system over that period of time. This book t...
Price: $76.50 | Publisher: Wiley | Release: 2012
Machine Learning for Decision Makers
by Patanjali Kashyap
Take a deep dive into the concepts of machine learning as they apply to contemporary business and management. You will learn how machine learning techniques are used to solve fundamental and complex problems in society and industry. Machine Learning for Decision Makers serves as an excellent resource for establishing the relationship of m...
Price: $29.99 | Publisher: Apress | Release: 2017
AI-Powered Business Intelligence
by Tobias Zwingmann
Use business intelligence to power corporate growth, increase efficiency, and improve corporate decision making. With this practical book with hands-on examples in Power BI, you'll explore the most relevant AI use cases for BI, including improved forecasting, automated classification, and AI-powered recommendations. And you'll l...
Price: $45.95 | Publisher: O'Reilly Media | Release: 2022
Beginning Azure Cognitive Services
by Alicia Moniz, Matt Gordon, Ida Bergum, Mia Chang, Ginger Grant
Get started with Azure Cognitive Services and its APIs that expose machine learning as a service. This book introduces the suite of Azure Cognitive Services and helps you take advantage of the proven machine learning algorithms that have been developed by experts and made available through Cognitive Services, easily integrating those algo...
Price: $51.91 | Publisher: Apress | Release: 2021
Data Science Algorithms in a Week, 2nd Edition
by David Natingga
Machine learning applications are highly automated and self-modifying, and continue to improve over time with minimal human intervention, as they learn from the trained data. To address the complex nature of various real-world data problems, specialized machine learning algorithms have been developed. Through algorithmic and statistical a...
Price: $39.99 | Publisher: Packt Publishing | Release: 2018
Distributed Graph Algorithms for Computer Networks
by Kayhan Erciyes
This hands-on textbook/reference presents a comprehensive review of key distributed graph algorithms for computer network applications, with a particular emphasis on practical implementation. Each chapter opens with a concise introduction to a specific problem, supporting the theory with numerous examples, before providing a list of relev...
Price: $55.20 | Publisher: Springer | Release: 2013
Modern Algorithms for Image Processing
by Vladimir Kovalevsky
Utilize modern methods for digital image processing and take advantage of the many time-saving templates provided for all of the projects in this book.Modern Algorithms for Image Processing approaches the topic of image processing through teaching by example. Throughout the book, you will create projects that resolve typical problems that...
Price: $37.99 | Publisher: Apress | Release: 2019
by Jayani Withanawasam
Apache Mahout is a scalable machine learning library with algorithms for clustering, classification, and recommendations. It empowers users to analyze patterns in large, diverse, and complex datasets faster and more scalably.This book is an all-inclusive guide to analyzing large and complex datasets using Apache Mahout. It explains compli...
Price: $24.99 | Publisher: Packt Publishing | Release: 2015