Handbook Of Machine Learning - Volume 2: Optimization And Decision Making PDF Download
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Author: Tshilidzi Marwala
Publisher: World Scientific
ISBN: 981120568X
Category : Computers
Languages : en
Pages : 321
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Book Description
Building on , this volume on Optimization and Decision Making covers a range of algorithms and their applications. Like the first volume, it provides a starting point for machine learning enthusiasts as a comprehensive guide on classical optimization methods. It also provides an in-depth overview on how artificial intelligence can be used to define, disprove or validate economic modeling and decision making concepts.
Author: Tshilidzi Marwala
Publisher: World Scientific
ISBN: 981120568X
Category : Computers
Languages : en
Pages : 321
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Book Description
Building on , this volume on Optimization and Decision Making covers a range of algorithms and their applications. Like the first volume, it provides a starting point for machine learning enthusiasts as a comprehensive guide on classical optimization methods. It also provides an in-depth overview on how artificial intelligence can be used to define, disprove or validate economic modeling and decision making concepts.
Author: Vishal Jain
Publisher: CRC Press
ISBN: 100045567X
Category : Business & Economics
Languages : en
Pages : 295
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Book Description
Technology is moving at an exponential pace in this era of computational intelligence. Machine learning has emerged as one of the most promising tools used to challenge and think beyond current limitations. This handbook will provide readers with a leading edge to improving their products and processes through optimal and smarter machine learning techniques. This handbook focuses on new machine learning developments that can lead to newly developed applications. It uses a predictive and futuristic approach, which makes machine learning a promising tool for processes and sustainable solutions. It also promotes newer algorithms that are more efficient and reliable for new dimensions in discovering other applications, and then goes on to discuss the potential in making better use of machines in order to ensure optimal prediction, execution, and decision-making. Individuals looking for machine learning-based knowledge will find interest in this handbook. The readership ranges from undergraduate students of engineering and allied courses to researchers, professionals, and application designers.
Author: Tshilidzi Marwala
Publisher: Springer Nature
ISBN: 9819792517
Category :
Languages : en
Pages : 251
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Book Description
Author: Tshilidzi Marwala
Publisher: Springer Nature
ISBN: 9819728274
Category :
Languages : en
Pages : 267
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Book Description
Author: Tshilidzi Marwala
Publisher: Academic Press
ISBN: 0128209445
Category : Science
Languages : en
Pages : 272
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Book Description
Intelligent machines are populating our social, economic and political spaces. These intelligent machines are powered by Artificial Intelligence technologies such as deep learning. They are used in decision making. One element of decision making is the issue of rationality. Regulations such as the General Data Protection Regulation (GDPR) require that decisions that are made by these intelligent machines are explainable. Rational Machines and Artificial Intelligence proposes that explainable decisions are good but the explanation must be rational to prevent these decisions from being challenged. Noted author Tshilidzi Marwala studies the concept of machine rationality and compares this to the rationality bounds prescribed by Nobel Laureate Herbert Simon and rationality bounds derived from the work of Nobel Laureates Richard Thaler and Daniel Kahneman. Rational Machines and Artificial Intelligence describes why machine rationality is flexibly bounded due to advances in technology. This effectively means that optimally designed machines are more rational than human beings. Readers will also learn whether machine rationality can be quantified and identify how this can be achieved. Furthermore, the author discusses whether machine rationality is subjective. Finally, the author examines whether a population of intelligent machines collectively make more rational decisions than individual machines. Examples in biomedical engineering, social sciences and the financial sectors are used to illustrate these concepts. - Provides an introduction to the key questions and challenges surrounding Rational Machines, including, When do we rely on decisions made by intelligent machines? What do decisions made by intelligent machines mean? Are these decisions rational or fair? Can we quantify these decisions? and Is rationality subjective? - Introduces for the first time the concept of rational opportunity costs and the concept of flexibly bounded rationality as a rationality of intelligent machines and the implications of these issues on the reliability of machine decisions - Includes coverage of Rational Counterfactuals, group versus individual rationality, and rational markets - Discusses the application of Moore's Law and advancements in Artificial Intelligence, as well as developments in the area of data acquisition and analysis technologies and how they affect the boundaries of intelligent machine rationality
Author: Tshilidzi Marwala
Publisher: Springer Nature
ISBN: 9819951038
Category : Political Science
Languages : en
Pages : 221
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Book Description
This book explores how AI and mechanism design can provide a new framework for international politics. The international political system is all manners in which countries, governments and people relate. Mechanism design in international politics relates to identifying rules that define relationships between people and countries that achieve a particular outcome, e.g., peace or more trade or democracy or economic development. Artificial intelligence is technique of making machines intelligent. This book explores mechanism design and artificial intelligence in international politics and applies these technologies to politics, economy and society. This book will be of interest to scholars of international relations, politics, sustainable development, and artificial intelligence.
Author: Bhaso Ndzendze
Publisher: World Scientific
ISBN: 9811234566
Category : Computers
Languages : en
Pages : 190
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Book Description
Artificial Intelligence and Emerging Technologies in International Relations explores the geopolitics between technology and international relations. Through a focus on war, trade, investment flows, diplomacy, regional integration and development cooperation, this book takes a holistic perspective to examine the origins of technology, analysing its current manifestations in the contemporary world. The authors present the possible future roles of artificial intelligence (AI) and other emerging technologies (including blockchain, 3D printing, 5G connectivity and the Internet of Things) in the context of global arena.This book is essential reading to all who seek to understand the reality of the inequitable distribution of these game-changing technologies that are shaping the world. Research questions as well as some policy options for the developing world are explored and the authors make the case for cooperation by the international community as we enter the fourth industrial revolution.
Author: Ming Xie
Publisher: World Scientific
ISBN: 9811232229
Category : Technology & Engineering
Languages : en
Pages : 403
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Book Description
This book lays a new foundation toward achieving artificial self-intelligence by future machines such as intelligent vehicles. Its chapters provide a broad coverage to the three key modules behind the design and development of intelligent vehicles for the ultimate purpose of actively ensuring driving safety as well as preventing accidents from all possible causes. Self-contained and unified in presentation, the book explains in details the fundamental solutions of vehicle's perception, vehicle's decision-making, and vehicle's action-taking in a pedagogic order.Besides the fundamental knowledge and concepts of intelligent vehicle's perception, decision and action, this book includes a comprehensive set of real-life application scenarios in which intelligent vehicles will play a major role or contribution. These case studies of real-life applications will help motivate students to learn this exciting subject. With concise and simple explanations, and boasting a rich set of graphical illustrations, the book is an invaluable source for both undergraduate and postgraduate courses, on artificial intelligence, intelligent vehicle, and robotics, which are offered in automotive engineering, computer engineering, electronic engineering, and mechanical engineering. In addition, the book will help strengthen the knowledge and skills of young researchers who want to venture into the research and development of artificial self-intelligence for intelligent vehicles of the future.Related Link(s)
Author: Mykel J. Kochenderfer
Publisher: MIT Press
ISBN: 0262047012
Category : Computers
Languages : en
Pages : 701
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Book Description
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.
Author: Andriy Burkov
Publisher:
ISBN: 9781999579500
Category : Machine learning
Languages : en
Pages : 141
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Book Description
Provides a practical guide to get started and execute on machine learning within a few days without necessarily knowing much about machine learning.The first five chapters are enough to get you started and the next few chapters provide you a good feel of more advanced topics to pursue.
