Heuristic & Constrained Search Books

The Psychology of Judgment and Decision Making

Scott Plous

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Customer Reviews:
Total reviews: 17 Average rating: 5.0 of 5

Judging Judgment and Decision Making 4 out of 5 stars.
8 of 11 people found this review helpful.

A decade ago Scott Plous produced a very readable summary of research in social psychology and (what is now known as) behavioral economics.
Our understanding of how people actually behave (as opposed to our theories as to how they should behave) has been immeasurably enriched by work dating (variously) from Herbert Simon, Daniel Kahneman, Amos Tversky, Stanley Milgram and many others.
Management education has yet to fully take into account the many insights coming from psychologists, experimental economists and others so nicely summarized in this book.

Editorial Review:

THE PSYCHOLOGY OF JUDGMENT AND DECISION MAKING offers a comprehensive introduction to the field with a strong focus on the social aspects of decision making processes. Winner of the prestigious William James Book Award, THE PSYCHOLOGY OF JUDGMENT AND DECISION MAKING is an informative and engaging introduction to the field written in a style that is equally accessible to the introductory psychology student, the lay person, or the professional. A unique feature of this volume is the Reader Survey which readers are to complete before beginning the book. The questions in the Reader Survey are drawn from many of the studies discussed throughout the book, allowing readers to compare their answers with the responses given by people in the original studies. This title is part of The McGraw-Hill Series in Social Psychology.

Judgment under Uncertainty: Heuristics and Biases

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Total reviews: 5 Average rating: 4.5 of 5

This is the best book I've ever seen about probability. 5 out of 5 stars.
75 of 94 people found this review helpful.

I've never seen better explanations of how probabilities should be calculated. And the book is fascinating -- especially what the authors describe about the results of surveys designed to reveal the most common mistakes people make when estimating probabilities.

Editorial Review:

The thirty-five chapters in this book describe various judgmental heuristics and the biases they produce, not only in laboratory experiments but in important social, medical, and political situations as well. Individual chapters discuss the representativeness and availability heuristics, problems in judging covariation and control, overconfidence, multistage inference, social perception, medical diagnosis, risk perception, and methods for correcting and improving judgments under uncertainty. About half of the chapters are edited versions of classic articles; the remaining chapters are newly written for this book. Most review multiple studies or entire subareas of research and application rather than describing single experimental studies. This book will be useful to a wide range of students and researchers, as well as to decision makers seeking to gain insight into their judgments and to improve them.

Heuristics and Biases: The Psychology of Intuitive Judgment

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Total reviews: 2 Average rating: 5.0 of 5

Of vast importance 5 out of 5 stars.
32 of 34 people found this review helpful.

This collection of articles has its origin in the work of one of the editors (Daniel Kahneman) and Amos Tversky (now deceased) in the 1970's. The first article in the book gives an introduction to this work and a brief historical survey. This work, along with current developments, is extremely important, for it sheds light on the differences (if any) between "intuitive judgment" and judgment that is based on more quantitative, mathematical, or algorithmic reasoning. If human judgment in uncertain environments is based on a limited number of simplifying heuristics, and not on extensive algorithmic processing, this would be very important for someone who is attempting to implement or simulate human reasoning in a machine. Economics, finance, and political decision-making are other areas that need a more accurate view of human judgment. Indeed, the "rational agent" assumption in classical economics, wherein the person makes choices by assessing the probability of each possible outcome and then assigning a utility to each, is considered to be fundamental, even axiomatic. It is therefore of great interest to examine challenges to this assumption.

In order to test the rational agent assumption, experiments must be conducted to test whether indeed the human assessment of likelihood and risk does indeed conform to the laws of probability. The data obtained in these experiments must then be judged as to whether it can be used to decide between the rational agent model and models of human judgment that are based on "intuition" (however vaguely or mystically this latter term is defined).

The authors of the first article in this book discuss some of the work on these questions, in particular the research that involved comparing expert clinical prediction with actuarial methods. The latter were found to perform better than the former. Even more interesting is that the clinician's assessments of their abilities were very far from what the record of success actually indicated. Some research has also indicated that intuitive judgments of likelihood do not correspond to what is obtained by Bayesian reasoning patterns.

These results, as the authors discuss, motivated performance models that were not based on the assumption of full rationality, but rather on what is called `bounded rationality.' The developers of this model felt that the processing limitations of the human brain dictated that humans must choose very limited heuristics when engaged in decision-making.

Also of great interest, and discussed in another article in the book, is the human ability to engage in affective forecasting. The latter involves the making of decisions based on the predictions of the emotional consequences of future events. The authors study the accuracy of affective forecasting and the accompanying notion of `durability bias.' The latter notion arises when individuals attempt to estimate how long particular feelings will last, and this estimation seems to be considerably longer than what actually occurs. The authors discuss some of the reasons for the durability bias in affective forecasting. One of these is ordinary misconstrual, where events are thought to be more powerful than what are actually realized, resulting in the overestimation of the duration of the affective responses to these events. Another regards the difficulty in forecasting affective reactions to events about which much is known. In addition, the authors point to "defensive pessimism" as to another of the reasons for inaccurate affective forecasting. This allows for mental preparation for the consequences of an event, and for positive feelings when the affective duration is smaller than what had been predicted. The main emphasis of the authors' article though is much more interesting than these explanations, for it involves the notion of a `psychological immune system.' Quoting the research of many psychologists, and arguing in analogy to the ordinary biological immune system, the authors view this system as one that protects the individual from an "overdose of gloom." Further, the functioning of the psychological immune system is optimized when it is not brought into the conscious focus of the individual. This `immune neglect' however has as a consequence the durability bias, in that if an individual fails to recognize her negative affect will decrease and be subjected to psychological mechanisms that assist greatly in this diminution, then she will tend to overestimate the time duration of her emotional reactions. The authors discuss empirical studies of durability bias in their article, and discuss some of the consequences of their studies. One of these concerns the possibility that humans could be mistaken about their own internal experiences. This is a very troubling possibility, but the authors give many references that purport to support it. This research shows that not only can people be completely mistaken about their feelings toward an object, but that their actual behaviors is better evidence of their internal states than what they report verbally.

Another interesting article in the book concerns the topic of automated choice heuristics. This area has arisen as a reaction to the idea that human choice can be predicted using theoretical models of optimal choice. Instead, one must identify the heuristics the people use to simplify their choices. These heuristics are used to restrict or compress the amount of information that is processed by the human brain and also to deal with the complexity in which this information is assimilated. There are many different theories of choice heuristics, and some of these are discussed in the article. Some of these theories involve heuristics that are "deliberate", i.e. involve the elimination of aspects and slower cognitive processes, and some involve heuristics that are "automatic" and judgmental, i.e. that arise from cognitive processes that are rapid and not controllable. Judgmental heuristics is also referred to as `System 1' heuristics in the article, whereas deliberate heuristics is referred to as `System 2' heuristics. The authors give a very interesting overview of automated choice heuristics, involving choices that are based on immediate affective evaluation, and choices that are using the option that is first thought of. All of these discussions, as are all the others in the book, are extremely important.

Editorial Review:

Judgment pervades human experience. Do I have a strong enough case to go to trial? Will the Fed change interest rates? Can I trust this person? This book examines how people answer such questions. How do people cope with the complexities of the world economy, the uncertain behavior of friends and adversaries, or their own changing tastes and personalities? When are people's judgments prone to bias, and what is responsible for their biases? This book compiles psychologists' best attempts to answer these important questions.

Simple Heuristics That Make Us Smart

Gerd Gigerenzer, Peter M. Todd, ABC Research Group

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Total reviews: 7 Average rating: 4.0 of 5

Editorial Review:

Simple Heuristics That Make Us Smart invites readers to embark on a new journey into a land of rationality that differs from the familiar territory of cognitive science and economics. Traditional views of rationality tend to see decision makers as possessing superhuman powers of reason, limitless knowledge, and all of eternity in which to ponder choices. To understand decisions in the real world, we need a different, more psychologically plausible notion of rationality, and this book provides it. It is about fast and frugal heuristics--simple rules for making decisions when time is pressing and deep thought an unaffordable luxury. These heuristics can enable both living organisms and artificial systems to make smart choices, classifications, and predictions by employing bounded rationality.
But when and how can such fast and frugal heuristics work? Can judgments based simply on one good reason be as accurate as those based on many reasons? Could less knowledge even lead to systematically better predictions than more knowledge? Simple Heuristics explores these questions, developing computational models of heuristics and testing them through experiments and analyses. It shows how fast and frugal heuristics can produce adaptive decisions in situations as varied as choosing a mate, dividing resources among offspring, predicting high school drop out rates, and playing the stock market.
As an interdisciplinary work that is both useful and engaging, this book will appeal to a wide audience. It is ideal for researchers in cognitive psychology, evolutionary psychology, and cognitive science, as well as in economics and artificial intelligence. It will also inspire anyone interested in simply making good decisions.

How to Solve It: Modern Heuristics

Zbigniew Michalewicz, David B. Fogel

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Customer Reviews:
Total reviews: 18 Average rating: 4.5 of 5

It's not the technique, it's the logic behind it 4 out of 5 stars.
6 of 8 people found this review helpful.

Most evolutionary computation or math books deal with the techniques of solving problems. This book teachs you how to think of a solution for the problem you face, and not what problems are appropriate for the technique in hand.

The logic is that when you do a craft work, you do pick the appropriate tool from your tools box, but you don't grasp a tool and then find a job to go with it, which is the case when you can only handle this tool.

Editorial Review:

This book is the only source that provides comprehensive, current, and correct information on problem solving using modern heuristics. It covers classic methods of optimization, including dynamic programming, the simplex method, and gradient techniques, as well as recent innovations such as simulated annealing, tabu search, and evolutionary computation. Integrated into the discourse is a series of problems and puzzles to challenge the reader. The book is written in a lively, engaging style and is intended for students and practitioners alike. Anyone who reads and understands the material in the book will be armed with the most powerful problem solving tools currently known.

This second edition contains two new chapters, one on coevolutionary systems and one on multicriterial decision-making. Also some new puzzles are added and various subchapters are revised.

Information Retrieval: Algorithms and Heuristics (The Information Retrieval Series)(2nd Edition)

David A. Grossman, Ophir Frieder

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Total reviews: 8 Average rating: 4.0 of 5

Editorial Review:

Interested in how an efficient search engine works? Want to know what algorithms are used to rank resulting documents in response to user requests? The authors answer these and other key information retrieval design and implementation questions.

This book is not yet another high level text. Instead, algorithms are thoroughly described, making this book ideally suited for both computer science students and practitioners who work on search-related applications. As stated in the foreword, this book provides a current, broad, and detailed overview of the field and is the only one that does so. Examples are used throughout to illustrate the algorithms.

The authors explain how a query is ranked against a document collection using either a single or a combination of retrieval strategies, and how an assortment of utilities are integrated into the query processing scheme to improve these rankings. Methods for building and compressing text indexes, querying and retrieving documents in multiple languages, and using parallel or distributed processing to expedite the search are likewise described.

This edition is a major expansion of the one published in 1998. Besides updating the entire book with current techniques, it includes new sections on language models, cross-language information retrieval, peer-to-peer processing, XML search, mediators, and duplicate document detection.

Methods of Discovery: Heuristics for the Social Sciences (Contemporary Societies)

Andrew Abbott

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Total reviews: 1 Average rating: 5.0 of 5

A Brilliant, Readable Introduction to the Logic of Sociology 5 out of 5 stars.
13 of 18 people found this review helpful.

This is a beautifully written, clear and understandable analysis of the diverse ways of thinking in contemporary sociology. It is written to be understandable by undergraduates who are serious about the discipline and are about to undertake research on their own. Graduate students will find it indispensible as they make very important decisions about their own careers. Reading Abbott is much easier than trying to figure these things out on your own . The author's concept of "fractual heuristics" is an innovative and insightful way of thinking about the interaction of different kinds of ideas in the discipline. There is too much here for me to summarize in a short review, but it is well worth reading.
Ted Goertzel, Professor of Sociology, Rutgers University.

Editorial Review:

Methods of Discovery is organized around strategies for deepening arguments in order to find the best ways to study social phenomena. This exciting book is not about the mechanics of doing social science research, but about habits of thinking that enable students to use those mechanics in new ways, by coming up with new ideas and combining them more effectively with old ones. Examples from throughout the social sciences help show how these moves can open new lines of thinking. Each chapter covers several moves and their reverses (if these exist), discussing particular examples of the move as well as its logical and theoretical structure. This book offers readers a new way of thinking about directions for their research and new ways to imagine information relevant to their research problems.

Heuristic Research: Design, Methodology, and Applications

Clark Moustakas

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Total reviews: 1 Average rating: 5.0 of 5

Qualitative Research Help 5 out of 5 stars.
4 of 4 people found this review helpful.

I chose a qualitative method for a research proposal and wanted to examine the data in a detailed, personal way. I purchased many books about various qualitative methods, but all of them failed to assist me. I finally came upon this book, and the author clearly outlined what is involved with this form of research--heuristic inquiry. It totally changed how I looked at the the transcripts of my participants, and assisted me in extracting rich themes and descriptions. I highly recommend this book to those who are serious about qualitative research, e.g., heuristic research, and are willing to do all that is required to complete a thesis or dissertation that they can be proud of for years to come.

Editorial Review:

Heuristic Research is a unique book in the area of qualitative research. Well organized and well referenced, it gives a clear presentation of heuristic methodology as a systematic form of research. Investigators of human experiences will find this book invaluable as a research guide.

The author illustrates how heuristic concepts and processes form components of the research design and become the basis for a methodology. There is a clear explanation of how heuristic inquiry works in practice and the actual process of conducting a human science investigation is described in detail.

Object-Oriented Design Heuristics

Arthur J. Riel

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Total reviews: 28 Average rating: 4.5 of 5

Editorial Review:

Upon completion of an object-oriented design, you are faced with a troubling question: "Is it good, bad, or somewhere in between?" Seasoned experts often answer this question by subjecting the design to a subconscious list of guidelines based on their years of experience. Experienced developer Arthur J. Riel has captured this elusive, subconscious list, and in doing so, has provided a set of metrics that help determine the quality of object-oriented models. Object-Oriented Design Heuristics offers insight into object-oriented design improvement. The more than sixty guidelines presented in this book are language-independent and allow you to rate the integrity of a software design. The heuristics are not written as hard and fast rules; they are meant to serve as warning mechanisms which allow the flexibility of ignoring the heuristic as necessary. This tutorial-based approach, born out of the author's extensive experience developing software, teaching thousands of students, and critiquing designs in a variety of domains, allows you to apply the guidelines in a personalized manner.The heuristics cover important topics ranging from classes and objects (with emphasis on their relationships including association, uses, containment, and both single and multiple inheritance) to physical object-oriented design. You will gain an understanding of the synergy that exists between design heuristics and the popular concept of design patterns; heuristics can highlight a problem in one facet of a design while patterns can provide the solution. Programmers of all levels will find value in this book. The newcomer will discover a fast track to understanding the concepts of object-oriented programming. At the same time, experienced programmers seeking to strengthen their object-oriented development efforts will appreciate the insightful analysis. In short, with Object-Oriented Design Heuristics as your guide, you have the tools to become a better software developer. 020163385XB04062001

Content Area Reading: A Heuristic Approach

Anthony V. Manzo, Ula Casale Manzo

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