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Algorithms for Decision Making

Mykel J. Kochenderfer,Tim A. Wheeler,Kyle H. Wray

Author : Mykel J. Kochenderfer,Tim A. Wheeler,Kyle H. Wray
Publisher : MIT Press
Page : 701 pages
File Size : 55,6 Mb
Release : 2022-08-16
Category : Computers
ISBN : 9780262047012

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Algorithms for Decision Making by Mykel J. Kochenderfer,Tim A. Wheeler,Kyle H. Wray Pdf

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.

Algorithms for Decision Making

Mykel J. Kochenderfer,Tim A. Wheeler,Kyle H. Wray

Author : Mykel J. Kochenderfer,Tim A. Wheeler,Kyle H. Wray
Publisher : MIT Press
Page : 701 pages
File Size : 43,7 Mb
Release : 2022-08-16
Category : Computers
ISBN : 9780262370233

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Algorithms for Decision Making by Mykel J. Kochenderfer,Tim A. Wheeler,Kyle H. Wray Pdf

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.

Algorithms in Decision Support Systems

Vicente García-Díaz

Author : Vicente García-Díaz
Publisher : MDPI
Page : 162 pages
File Size : 50,9 Mb
Release : 2021-03-19
Category : Technology & Engineering
ISBN : 9783036505886

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Algorithms in Decision Support Systems by Vicente García-Díaz Pdf

This book aims to provide a new vision of how algorithms are the core of decision support systems (DSSs), which are increasingly important information systems that help to make decisions related to unstructured and semi-unstructured decision problems that do not have a simple solution from a human point of view. It begins with a discussion of how DSSs will be vital to improving the health of the population. The following article deals with how DSSs can be applied to improve the performance of people doing a specific task, like playing tennis. It continues with a work in which authors apply DSSs to insect pest management, together with an interactive platform for fitting data and carrying out spatial visualization. The next article improves how to reschedule trains whenever disturbances occur, together with an evaluation framework. The final works focus on different relevant areas of DSSs: 1) a comparison of ensemble and dimensionality reduction models based on an entropy criterion; 2) a radar emitter identification method based on semi-supervised and transfer learning; 3) design limitations, errors, and hazards in creating very large-scale DSSs; and 4) efficient rule generation for associative classification. We hope you enjoy all the contents in the book.

After the Digital Tornado

Kevin Werbach

Author : Kevin Werbach
Publisher : Cambridge University Press
Page : 251 pages
File Size : 41,7 Mb
Release : 2020-07-23
Category : Computers
ISBN : 9781108426633

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After the Digital Tornado by Kevin Werbach Pdf

Leading technology scholars examine how networks powered by algorithms are transforming humanity, posing deep questions about power, freedom, and fairness. This title is also available as Open Access on Cambridge Core.

Decision Making Under Uncertainty

Mykel J. Kochenderfer

Author : Mykel J. Kochenderfer
Publisher : MIT Press
Page : 350 pages
File Size : 40,5 Mb
Release : 2015-07-24
Category : Computers
ISBN : 9780262331715

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Decision Making Under Uncertainty by Mykel J. Kochenderfer Pdf

An introduction to decision making under uncertainty from a computational perspective, covering both theory and applications ranging from speech recognition to airborne collision avoidance. Many important problems involve decision making under uncertainty—that is, choosing actions based on often imperfect observations, with unknown outcomes. Designers of automated decision support systems must take into account the various sources of uncertainty while balancing the multiple objectives of the system. This book provides an introduction to the challenges of decision making under uncertainty from a computational perspective. It presents both the theory behind decision making models and algorithms and a collection of example applications that range from speech recognition to aircraft collision avoidance. Focusing on two methods for designing decision agents, planning and reinforcement learning, the book covers probabilistic models, introducing Bayesian networks as a graphical model that captures probabilistic relationships between variables; utility theory as a framework for understanding optimal decision making under uncertainty; Markov decision processes as a method for modeling sequential problems; model uncertainty; state uncertainty; and cooperative decision making involving multiple interacting agents. A series of applications shows how the theoretical concepts can be applied to systems for attribute-based person search, speech applications, collision avoidance, and unmanned aircraft persistent surveillance. Decision Making Under Uncertainty unifies research from different communities using consistent notation, and is accessible to students and researchers across engineering disciplines who have some prior exposure to probability theory and calculus. It can be used as a text for advanced undergraduate and graduate students in fields including computer science, aerospace and electrical engineering, and management science. It will also be a valuable professional reference for researchers in a variety of disciplines.

Algorithms to Live By

Brian Christian,Tom Griffiths

Author : Brian Christian,Tom Griffiths
Publisher : Penguin
Page : 438 pages
File Size : 41,9 Mb
Release : 2016-04-26
Category : Psychology
ISBN : 9780143196471

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Algorithms to Live By by Brian Christian,Tom Griffiths Pdf

A fascinating exploration of how computer algorithms can be applied to our everyday lives, helping to solve common decision-making problems and illuminate the workings of the human mind All our lives are constrained by limited space and time, limits that give rise to a particular set of problems. What should we do, or leave undone, in a day or a lifetime? How much messiness should we accept? What balance of new activities and familiar favourites is the most fulfilling? These may seem like uniquely human quandaries, but they are not: computers, too, face the same constraints, so computer scientists have been grappling with their version of such problems for decades. And the solutions they've found have much to teach us. In a dazzlingly interdisciplinary work, acclaimed author Brian Christian (who holds degrees in computer science, philosophy, and poetry, and works at the intersection of all three) and Tom Griffiths (a UC Berkeley professor of cognitive science and psychology) show how the simple, precise algorithms used by computers can also untangle very human questions. They explain how to have better hunches and when to leave things to chance, how to deal with overwhelming choices and how best to connect with others. From finding a spouse to finding a parking spot, from organizing one's inbox to understanding the workings of human memory, Algorithms to Live By transforms the wisdom of computer science into strategies for human living.

Decision Making, Models and Algorithms

Saul I. Gass

Author : Saul I. Gass
Publisher : Wiley-Interscience
Page : 440 pages
File Size : 54,7 Mb
Release : 1985-05-10
Category : Business & Economics
ISBN : STANFORD:36105040049343

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Decision Making, Models and Algorithms by Saul I. Gass Pdf

The first book to integrate the decision-making process through mathematical modelling. Using the concept of a decision framework, the ideas of decision making, models, and algorithms are introduced to the reader by way of realistic and entertaining problems. The structure, form, illustrations, problems, and challenges in this book provide a unique presentation of the subject matter.

A Human's Guide to Machine Intelligence

Kartik Hosanagar

Author : Kartik Hosanagar
Publisher : Penguin
Page : 274 pages
File Size : 46,8 Mb
Release : 2019-03-12
Category : Business & Economics
ISBN : 9780525560890

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A Human's Guide to Machine Intelligence by Kartik Hosanagar Pdf

A Wharton professor and tech entrepreneur examines how algorithms and artificial intelligence are starting to run every aspect of our lives, and how we can shape the way they impact us Through the technology embedded in almost every major tech platform and every web-enabled device, algorithms and the artificial intelligence that underlies them make a staggering number of everyday decisions for us, from what products we buy, to where we decide to eat, to how we consume our news, to whom we date, and how we find a job. We've even delegated life-and-death decisions to algorithms--decisions once made by doctors, pilots, and judges. In his new book, Kartik Hosanagar surveys the brave new world of algorithmic decision-making and reveals the potentially dangerous biases they can give rise to as they increasingly run our lives. He makes the compelling case that we need to arm ourselves with a better, deeper, more nuanced understanding of the phenomenon of algorithmic thinking. And he gives us a route in, pointing out that algorithms often think a lot like their creators--that is, like you and me. Hosanagar draws on his experiences designing algorithms professionally--as well as on history, computer science, and psychology--to explore how algorithms work and why they occasionally go rogue, what drives our trust in them, and the many ramifications of algorithmic decision-making. He examines episodes like Microsoft's chatbot Tay, which was designed to converse on social media like a teenage girl, but instead turned sexist and racist; the fatal accidents of self-driving cars; and even our own common, and often frustrating, experiences on services like Netflix and Amazon. A Human's Guide to Machine Intelligence is an entertaining and provocative look at one of the most important developments of our time and a practical user's guide to this first wave of practical artificial intelligence.

Noise

Daniel Kahneman,Olivier Sibony,Cass R. Sunstein

Author : Daniel Kahneman,Olivier Sibony,Cass R. Sunstein
Publisher : Little, Brown
Page : 429 pages
File Size : 43,7 Mb
Release : 2021-05-18
Category : Business & Economics
ISBN : 9780316451383

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Noise by Daniel Kahneman,Olivier Sibony,Cass R. Sunstein Pdf

From the Nobel Prize-winning author of Thinking, Fast and Slow and the coauthor of Nudge, a revolutionary exploration of why people make bad judgments and how to make better ones—"a tour de force” (New York Times). Imagine that two doctors in the same city give different diagnoses to identical patients—or that two judges in the same courthouse give markedly different sentences to people who have committed the same crime. Suppose that different interviewers at the same firm make different decisions about indistinguishable job applicants—or that when a company is handling customer complaints, the resolution depends on who happens to answer the phone. Now imagine that the same doctor, the same judge, the same interviewer, or the same customer service agent makes different decisions depending on whether it is morning or afternoon, or Monday rather than Wednesday. These are examples of noise: variability in judgments that should be identical. In Noise, Daniel Kahneman, Olivier Sibony, and Cass R. Sunstein show the detrimental effects of noise in many fields, including medicine, law, economic forecasting, forensic science, bail, child protection, strategy, performance reviews, and personnel selection. Wherever there is judgment, there is noise. Yet, most of the time, individuals and organizations alike are unaware of it. They neglect noise. With a few simple remedies, people can reduce both noise and bias, and so make far better decisions. Packed with original ideas, and offering the same kinds of research-based insights that made Thinking, Fast and Slow and Nudge groundbreaking New York Times bestsellers, Noise explains how and why humans are so susceptible to noise in judgment—and what we can do about it.

Decision Making in Medicine

Stuart B. Mushlin,Harry L. Greene

Author : Stuart B. Mushlin,Harry L. Greene
Publisher : Elsevier Health Sciences
Page : 754 pages
File Size : 49,7 Mb
Release : 2009-10-27
Category : Medical
ISBN : 9780323041072

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Decision Making in Medicine by Stuart B. Mushlin,Harry L. Greene Pdf

This popular reference facilitates diagnostic and therapeutic decision making for a wide range of common and often complex problems faced in outpatient and inpatient medicine. Comprehensive algorithmic decision trees guide you through more than 245 disorders organized by sign, symptom, problem, or laboratory abnormality. The brief text accompanying each algorithm explains the key steps of the decision making process, giving you the clear, clinical guidelines you need to successfully manage even your toughest cases. An algorithmic format makes it easy to apply the practical, decision-making approaches used by seasoned clinicians in daily practice. Comprehensive coverage of general and internal medicine helps you successfully diagnose and manage a full range of diseases and disorders related to women's health, emergency medicine, urology, behavioral medicine, pharmacology, and much more. A Table of Contents arranged by organ system helps you to quickly and easily zero in on the information you need. More than a dozen new topics focus on the key diseases and disorders encountered in daily practice. Fully updated decision trees guide you through the latest diagnostic and management guidelines.

Multicriteria Decision Making

Tomas Gal,Theodor Stewart,Thomas Hanne

Author : Tomas Gal,Theodor Stewart,Thomas Hanne
Publisher : Springer Science & Business Media
Page : 549 pages
File Size : 40,8 Mb
Release : 2013-03-09
Category : Business & Economics
ISBN : 9781461550259

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Multicriteria Decision Making by Tomas Gal,Theodor Stewart,Thomas Hanne Pdf

At a practical level, mathematical programming under multiple objectives has emerged as a powerful tool to assist in the process of searching for decisions which best satisfy a multitude of conflicting objectives, and there are a number of distinct methodologies for multicriteria decision-making problems that exist. These methodologies can be categorized in a variety of ways, such as form of model (e.g. linear, non-linear, stochastic), characteristics of the decision space (e.g. finite or infinite), or solution process (e.g. prior specification of preferences or interactive). Scientists from a variety of disciplines (mathematics, economics and psychology) have contributed to the development of the field of Multicriteria Decision Making (MCDM) (or Multicriteria Decision Analysis (MCDA), Multiattribute Decision Making (MADM), Multiobjective Decision Making (MODM), etc.) over the past 30 years, helping to establish MCDM as an important part of management science. MCDM has become a central component of studies in management science, economics and industrial engineering in many universities worldwide. Multicriteria Decision Making: Advances in MCDM Models, Algorithms, Theory and Applications aims to bring together `state-of-the-art' reviews and the most recent advances by leading experts on the fundamental theories, methodologies and applications of MCDM. This is aimed at graduate students and researchers in mathematics, economics, management and engineering, as well as at practicing management scientists who wish to better understand the principles of this new and fast developing field.

Thinking in Algorithms

Albert Rutherford

Author : Albert Rutherford
Publisher : Unknown
Page : 119 pages
File Size : 53,8 Mb
Release : 2021-10-02
Category : Electronic
ISBN : 9798488550544

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Thinking in Algorithms by Albert Rutherford Pdf

Think creatively like a human. Analyze and solve problems efficiently like a computer. Our everyday lives are filled with inefficient and ineffective decisions and solutions. Being overwhelmed by the magnitude of our problems makes it hard to think clearly. We procrastinate and overthink. Our thoughts are tainted with biases. If only there was a way to simplify our decision-making and problem-solving process and get satisfying, consistent results! The good news is, there is! Apply computer algorithms to your everyday problems. Learn what algorithms are and use them for better decision-making, problem-solving, and staying on track with your plans. Become more productive, organized, finish what you start, and make better decisions. If you feel that you're not living up to your potential, struggle with being consistent about your habits, and would like to make quicker and better decisions, this book is for you! Get things started immediately and finish them within your deadline. Thinking in Algorithms presents research and scientific studies on behavioral economics, cognitive science, and neuropsychology about what constitutes a great decision, what are and how to manage its roadblocks. This is an interdisciplinary work that will help you learn how to apply computer algorithm-based solutions to your life challenges. Know when to stop. Be efficient with your time and energy. Albert Rutherford is an internationally bestselling author whose writing derives from various sources, such as research, coaching, academic and real-life experience. Machine learning principles for the laymen. - Learn to build your own problem-solving algorithms using a unique formula. - The science of optimal stopping. - How to overcome procrastination and overthinking using algorithms. Help your emotional, biased brain to make more rational and predictable decisions and follow through plans using algorithm-based problem-solving today! Not convinced yet? Check out the look inside feature of this book hitting the top left corner of this page and read the first pages for free!

The Cambridge Handbook of the Law of Algorithms

Woodrow Barfield

Author : Woodrow Barfield
Publisher : Cambridge University Press
Page : 0 pages
File Size : 51,6 Mb
Release : 2023-03-30
Category : Law
ISBN : 100929315X

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The Cambridge Handbook of the Law of Algorithms by Woodrow Barfield Pdf

Algorithms are a fundamental building block of artificial intelligence - and, increasingly, society - but our legal institutions have largely failed to recognize or respond to this reality. The Cambridge Handbook of the Law of Algorithms, which features contributions from US, EU, and Asian legal scholars, discusses the specific challenges algorithms pose not only to current law, but also - as algorithms replace people as decision makers - to the foundations of society itself. The work includes wide coverage of the law as it relates to algorithms, with chapters analyzing how human biases have crept into algorithmic decision-making about who receives housing or credit, the length of sentences for defendants convicted of crimes, and many other decisions that impact constitutionally protected groups. Other issues covered in the work include the impact of algorithms on the law of free speech, intellectual property, and commercial and human rights law.

Algorithms for Optimization

Mykel J. Kochenderfer,Tim A. Wheeler

Author : Mykel J. Kochenderfer,Tim A. Wheeler
Publisher : MIT Press
Page : 521 pages
File Size : 50,7 Mb
Release : 2019-03-12
Category : Computers
ISBN : 9780262039420

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Algorithms for Optimization by Mykel J. Kochenderfer,Tim A. Wheeler Pdf

A comprehensive introduction to optimization with a focus on practical algorithms for the design of engineering systems. This book offers a comprehensive introduction to optimization with a focus on practical algorithms. The book approaches optimization from an engineering perspective, where the objective is to design a system that optimizes a set of metrics subject to constraints. Readers will learn about computational approaches for a range of challenges, including searching high-dimensional spaces, handling problems where there are multiple competing objectives, and accommodating uncertainty in the metrics. Figures, examples, and exercises convey the intuition behind the mathematical approaches. The text provides concrete implementations in the Julia programming language. Topics covered include derivatives and their generalization to multiple dimensions; local descent and first- and second-order methods that inform local descent; stochastic methods, which introduce randomness into the optimization process; linear constrained optimization, when both the objective function and the constraints are linear; surrogate models, probabilistic surrogate models, and using probabilistic surrogate models to guide optimization; optimization under uncertainty; uncertainty propagation; expression optimization; and multidisciplinary design optimization. Appendixes offer an introduction to the Julia language, test functions for evaluating algorithm performance, and mathematical concepts used in the derivation and analysis of the optimization methods discussed in the text. The book can be used by advanced undergraduates and graduate students in mathematics, statistics, computer science, any engineering field, (including electrical engineering and aerospace engineering), and operations research, and as a reference for professionals.

Randomized Algorithms

Rajeev Motwani,Prabhakar Raghavan

Author : Rajeev Motwani,Prabhakar Raghavan
Publisher : Cambridge University Press
Page : 496 pages
File Size : 43,7 Mb
Release : 1995-08-25
Category : Computers
ISBN : 0521474655

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Randomized Algorithms by Rajeev Motwani,Prabhakar Raghavan Pdf

This book presents basic tools from probability theory used in algorithmic applications, with concrete examples.

Algorithms For Decision Making

Algorithms for Decision Making by Mykel J. Kochenderfer,Tim A. Wheeler,Kyle H. Wray Pdf

Algorithms for Decision Making by Mykel J. Kochenderfer,Tim A. Wheeler,Kyle H. Wray Pdf

Algorithms in Decision Support Systems by Vicente García-Díaz Pdf

After the Digital Tornado by Kevin Werbach Pdf

Decision Making Under Uncertainty by Mykel J. Kochenderfer Pdf

Algorithms to Live By by Brian Christian,Tom Griffiths Pdf

Decision Making, Models and Algorithms by Saul I. Gass Pdf

A Human's Guide to Machine Intelligence by Kartik Hosanagar Pdf

Noise by Daniel Kahneman,Olivier Sibony,Cass R. Sunstein Pdf

Decision Making in Medicine by Stuart B. Mushlin,Harry L. Greene Pdf

Multicriteria Decision Making by Tomas Gal,Theodor Stewart,Thomas Hanne Pdf

Thinking in Algorithms by Albert Rutherford Pdf

The Cambridge Handbook of the Law of Algorithms by Woodrow Barfield Pdf

Algorithms for Optimization by Mykel J. Kochenderfer,Tim A. Wheeler Pdf

Randomized Algorithms by Rajeev Motwani,Prabhakar Raghavan Pdf

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