Customer Reviews

Simple Heuristics That Make Us Smart (Evolution and Cognition Series)

5 star:		(4)
4 star:		(3)
3 star:		(0)
2 star:		(1)
1 star:		(1)

 

 

Whether you like a book depends on what information you're looking for. i make computer models of human behavior so this book, which is easy to read but filled with concrete solutions and lots of supporting dat, was near-perfect for me

As a note, i'm picky when it comes both to writing and thinking. And i hate most books written by academics. Even the ones with good information (eg, Fodor's Modularity) are hard to read and filled with confusing, field-specific words. Not this book. It's really well written. Written in plain English, very few assumptions, very thorough analysis, lots of self-criticism, lots and lots of data (OK, that part is boring and can be skipped, but it's comforting to know it's there)

What's it about? Common AI, psych and economic decision and learning algorithms (decision trees, neural nets, Bayes, multiple linear regression, etc.) are compared to several absurdly simple algorithms the authors believe real humans use. The various approaches are compared and evaluated on the basis of performance, accuracy on training data, accuracy on test data (generalization) and amount of input data required. Tests are on the standard UC Irvine data learning test sets. Comparisions, outcome explanations and relevance to the human mind and the real world are provided. Explanations and analysises are easy to understand and pretty convincing

i've decided to use a lot of what was in this book in my software, things that have made my agents more natural and easier to implement. i absolutely love this book

As someone interested in the practice and theory of decision making, I came upon this book via a number of "listmania" lists that reccomend it. The first few chapters got me excited about the subject matter. The authors promised to present a new model for decision making, one that was simple, and one that works.

The ensuing pages compare several theoretical models, such as Multiple Linear Regression and Dawes Rule to their own Take the First and Take the Best models.

Most of the tests were simulated on a computer. You would feed each decision making model into the computer, and then feed in various data for it to make decisions on. One popular test is "Which is the most populated German City." The computer had data on various German Cities with populations over 100,000. It also had several indicators, such as whether it has a soccer team, or a rail system, or is a state capital. The system would present two cities, with the indicators, and the decision making model would figure out which was the most populous one.

Right now I'm in a chapter called "Bayesian Benchmarks for Fast and Frugal Heuristics." It's about halfway through the book, and I'm not sure I'll finish. While the second half sounds interesting, this book is highly academic and the authors are concerned with presenting proofs for everything they say, in detail. Sort of like a victorian novel that starts of by telling you what it's going to tell you, and then tells you several times. I may skim it because I do find the subject matter intereting.

I certainly don't regret buying this book, having mathematical models for decision making is certainly handy (as someone interested in AI), but I wouldn't call it light reading, nor would I reccomend it to a manager interested in the decision making process.

I found much more interesting "Sources of Power" by Gary Klein. Indeed, I consider Sources of Power to be one of the most informative and most entertaining books I've ever read, and wish more like it existed.

In summation, I found this book to be highly academic and theoretical. If you are a human being interested in the decision making process as it is carried out by humans, I reccomend the more hands-on Sources of Power by Gary Klein. If you are interested in simple, statistical models for decision making (the kind you can teach a computer), then pick up this book.

This book introduced me to an exciting new way of thinking about decision making. "Heuristics" is basically just a fancy word for "rules of thumb" and the book shows convincingly how simple rules of thumb can go a very long way.

The 18 authors from various academic fields believe that decision rules and the environment in which they are used should always be considered together. Moreover it seems plausible that a simple rule which performs as well as a rule that requires more effort to apply, should be the preferred way of explaining the observed behavior.

The authors propose a bunch of simple heuristics for all kinds of problems. One particularly impressive example was the extremely simple "recognition heuristic" which e.g. proved to be quite successful on the stock market. For all heuristics in the book it is shown that they are easy to use, that they require little memory and computational capacity, and that therefore they appear to be very plausible models for explaining human (and animal) behavior.

If you are interested in decision making and/or if you are working in the fields of psychology, economics, artificial intelligence or related fields, this book is a "must-have"!

Gerd Gigerenzer is probably THE guru in heuristics - the art of picking a few shorthand rules to help us make complex decisions - but I found other works of his (Adaptive Thinking, Bounded Rationality) pretty dry going. By contrast this volume - a collection of stimulating, sometimes provocative essays by members of the ABC Research group (the centrer for Adaptive Behavior and Cognition) explores many facets of Heuristics and even puts heuristics to the test against other more computationally complex techniques to pick the outcomes for several complicated problems. Time and again, the simple rules of thumb out-perform the grindingly thorough statistical routines. For anyone researching human behaviour, the implicit challenge is to stop asking huge batteries of questions - and to look instead for the little telltale rules by which people navigate their complicated environments.

I'd say that if you were just starting to look at heuristics, then this this volume of essays would be a good starting point. Even if you skip the super-technical pieces, there's plenty of thought provoking material written in a lively, unexpectedly "human" style.

People aren't computers. Human beings live in a real world of scarcity and constraint. Even though time and information may be scarce, human beings must make high-stakes decisions. Probability and logic offer models for the thought process of choosing between alternatives, but decision makers often do not have enough hours, data and skill to use these sophisticated approaches. Fortunately, some rough and ready cognitive shortcuts perform as well as or better than the most elaborately sophisticated models - at least in the real world context of limited information and time. Working with the ABC Research Group, authors Gerd Gigerenzer and Peter M. Todd explore some of those shortcuts, called "heuristics." They discuss in length and depth a series of experiments that demonstrate the value of heuristics. This is not light reading. It requires a level of comfort with academic style, mathematics and symbolic logic. Readers unfamiliar with cognition literature may find it a struggle - but we believes that those who persevere will find enough new insight to make the effort worthwhile.

It's really meant for a technical audience since this stuff is so cutting edge, but you shouldn't wait till the results appear in Time magazine. The experiments and writing are very easy to understand, very clear. And you will be amazed by the simple ways in which our brain takes shortcuts in reasoning -- both making it stupid and making it smart. Be careful next time you try to reason using probabilities, you're better off using frequency.

My own background is in philosophy, where this type of work has been very important in undermining the assumption that humans are rational. We aren't. You should probably read Kahnemann and Tversky's books before coming to this though, since this work adds an interesting spin to the old irrationality debate: maybe some of it is GOOD for us!

This book presents serious arguments in favor of using simple rules to make most decisions. They present many examples where getting a quick answer by evaluating a minimal amount of data produces almost as accurate a result as highly sophisticated models. They point out that ignoring information can minimize some biases: "people seldom consider more than one or two factors at any one time, although they feel that they can take a host of factors into account". (Tetlock makes similar suggestions in Expert Political Judgment).

They appear to overstate the extent to which their evidence generalizes. They test their stock market heuristic on a mere six months worth of data. If they knew much about stock markets, they'd realize that there are a lot more bad heuristics which work for a few years at a time than there are good heuristics. I'll bet that theirs will do worse than random in most decades.

The book's conclusions can be understood by skimming small parts of the book. Most of the book is devoted to detailed discussions of the evidence. I suggest following the book's advice when reading it - don't try to evaluate all the evidence, just pick out a few pieces.

This book reads like a PhD thesis re-written for mass consumption. All the statistics are coma-inducing and I felt like I had to hunt for useful information. I don't recommend it for the Kindle because some of the most useful information was presented in tiny charts which render poorly on my Gen II.

I give it two stars because it presents a truly innovative approach to the science of decision making and, though almost impossible to finish, it taught me something new.

I agree with most of the other reviews that the book is well written but will likely be enjoyed only by those who are interested in a more academic approach to the subject. I am giving this book one star primarily because of the authors' decision to price the Kindle version of this book at $26.00. I ordered the book at Barnes and Noble (and read about half of it the day it came in) but held off buying it because I saw on my cell phone that a Kindle version was available. What I missed was the $26.00 purchase price. Shame on you. The whole idea of Kindle is that the author's costs are practically eliminated, and that this savings is shared with the purchaser. $26.00 is just plain greedy. This is one customer you will not be profiting from. I will finish reading the book at the library or book store.