{"id":2497,"date":"2011-05-25T14:39:08","date_gmt":"2011-05-25T18:39:08","guid":{"rendered":"http:\/\/www.decisionsciencenews.com\/?p=2497"},"modified":"2011-06-02T11:38:30","modified_gmt":"2011-06-02T15:38:30","slug":"heuristics-the-foundations-of-adaptive-behavior","status":"publish","type":"post","link":"https:\/\/www.decisionsciencenews.com\/?p=2497","title":{"rendered":"Heuristics: The foundations of adaptive behavior"},"content":{"rendered":"

HOW DO PEOPLE MAKE DECISIONS WHEN TIME IS LIMITED, INFORMATION UNRELIABLE, AND THE FUTURE UNCERTAIN?<\/p>\n

\"\"<\/a><\/p>\n

A new reader on heuristics, Heuristics: The Foundations of Adaptive Behavior<\/a>\"\", has just been released. Full disclosure, your Decision Science News editor is author on two of the book’s chapters<\/em>:<\/p>\n

CITATION:<\/p>\n

Gigerenzer, G., Hertwig, R., & Pachur, T. (Eds.). (2011). Heuristics: The Foundations of Adaptive Behavior<\/a>. New York: Oxford University Press.<\/p>\n

 <\/p>\n

PRECIS:<\/p>\n

How do people make decisions when time is limited, information unreliable, and the future uncertain?<\/p>\n

Based on the work of Nobel laureate Herbert Simon and with the help of colleagues around the world, the Adaptive Behavior and Cognition (ABC) Group at the Max Planck Institute for Human Development in Berlin has developed a research program on simple heuristics, also known as fast and frugal heuristics. In the social sciences, heuristics have been believed to be generally inferior to complex methods for inference, or even irrational.<\/p>\n

Although this may be true in “small worlds” where everything is known for certain, we show that in the actual world in which we live, full of uncertainties and surprises, heuristics are indispensable and often more accurate than complex methods. Contrary to a deeply entrenched belief, complex problems do not necessitate complex computations. Less can be more.\u00a0 Simple heuristics exploit the information structure of the environment, and thus embody ecological rather than logical rationality.<\/p>\n

Simon (1999) applauded this new program as a “revolution in cognitive science, striking a great blow for sanity in the approach to human rationality.” By providing a fresh look at how the mind works as well as the nature of rationality, the simple heuristics program has stimulated a large body of research, led to fascinating applications in diverse fields from law to medicine to business to sports, and instigated controversial debates in psychology, philosophy, and economics.<\/p>\n

In a single volume, the present reader compiles key articles that have been published in journals across many disciplines. These articles present theory, real-world applications, and a sample of the large number of existing experimental studies that provide evidence for people’s adaptive use of heuristics.<\/p>\n

Review:
\n“This volume makes a powerful case for the importance of fast and frugal heuristics in explaining a wide range of aspects of cognition. It brings together the latest developments in one of the most influential research programs in the decision sciences, and will provide a valuable stimulus for, and a challenge to, research across the field.”
\n— Nick Chater, Professor of Cognitive and Decision Sciences, University College London<\/p>\n

LINK
\nAmazon link to: Heuristics: The Foundations of Adaptive Behavior<\/a>\"\"<\/p>\n

TABLE OF CONTENTS<\/p>\n

Appetizer<\/p>\n

1. Homo heuristicus: Why Biased Minds Make Better Inferences.
\nGerd Gigerenzer, and Henry Brighton<\/p>\n

Part I: Theory<\/p>\n

Opening the adaptive toolbox<\/p>\n

2. Reasoning the Fast and Frugal Way: Models of Bounded Rationality.
\nGerd Gigerenzer, and Daniel G. Goldstein<\/p>\n

3. Models of Ecological Rationality: The Recognition Heuristic.
\nDaniel G. Goldstein and Gerd Gigerenzer<\/p>\n

4. How Forgetting Aids Heuristic Inference.
\nLael J. Schooler and R. Hertwig<\/p>\n

5. Simple Heuristics and Rules of Thumb: Where Psychologists and Behavioral Biologists Might Meet.
\nJohn M.C. Hutchinson and Gerd Gigerenzer<\/p>\n

6. Naive and Yet Enlightened: From Natural Frequencies to Fast and Frugal Decision Trees.
\nLaura Martignon, Oliver Vitouch, Masinori Takezawa, and Malcolm R. Forster<\/p>\n

7. The Priority Heuristic: Making Choices without Trade-Offs.
\nEduard Brandst\u00e4tter, Gerd Gigerenzer, and Ralph Hertwig<\/p>\n

8. One-Reason Decision making: Modeling Violations of Expected Utility Theory.
\nKonstantinos V. Katsikopoulos and Gerd Gigerenzer<\/p>\n

9. The Similarity Heuristic.
\nDaniel Read and Yael Grushka-Cockayne<\/p>\n

10. Hindsight Bias: A By-Product of Knowledge Updating?
\nUlrich Hoffrage, Ralph Hertwig, and Gerd Gigerenzer<\/p>\n

How are heuristics selected?<\/p>\n

11. SSL: A Theory of How People Learn to Select Strategies.
\nJ\u00f6rg Rieskamp and Philipp E. Otto<\/p>\n

Part II: Tests<\/p>\n

When do heuristics work?<\/p>\n

12. Fast, Frugal, and Fit: Simple Heuristics for Paired Comparison.
\nLaura Martignon and Ulrich Hoffrage<\/p>\n

13. Heuristic and Linear Models of Judgment: Matching Rules and Environments.
\nRobin M. Hogarth and Natalia Karelaia<\/p>\n

14. Categorization with Limited Resources: A Family of Simple Heuristics.
\nLaura Martignon, Konstantinos V. Katsikopoulo, and Jan K. Woike<\/p>\n

15. A Signal Detection Analysis of the Recognition Heuristic.
\nTimothy J. Pleskac<\/p>\n

16. The Relative Success of Recognition-Based Iinference in Multichoice Decisions.
\nRachel McCloy, C. Philip Beaman, and Philip T. Smith<\/p>\n

When do people rely on one good reason?<\/p>\n

17. The Quest for Take-the-Best.
\nArndt Br\u00f6der<\/p>\n

18. Empirical Tests of a Fast and Frugal Heuristic: Not Everyone “Takes-the-Best.”
\nBen R. Newell, Nicola J. Weston, and David R. Shanks<\/p>\n

19. A Response-Time Approach to Comparing Generalized Rational and Take-the-Best Models of Decision Making.
\nF. Bryan Bergert and Robert M. Nosofsky<\/p>\n

20. Sequential Processing of Cues in Memory-Based Multi-Attribute Decisions.
\nArndt Br\u00f6der and Wolfgang Gaissmaier<\/p>\n

21. Does Imitation Benefit Cue-OrderLlearning?
\nRocio Garcia-Retamero, Masanori Takezawa, and Gerd Gigerenzer<\/p>\n

22. The Aging Decision Maker: Cognitive Aging and the Adaptive Selection of Decision Strategies.
\nRui Mata, Lael J. Schooler, and J\u00f6rg Rieskamp<\/p>\n

When do people rely on name recognition?<\/p>\n

23. On the Psychology of the Recognition Heuristic: Retrieval Primacy as a Key Determinant of its Use.
\nThorsten Pachur and Ralph Hertwig<\/p>\n

24. The Recognition Heuristic in Memory-Based Inference: Is Recognition a Non-Compensatory Cue?
\nThorsten Pachur, Arndt Br\u00f6der, and Julian N. Marewski<\/p>\n

25. Why You Think Milan is Larger than Modena: Neural Correlates of the Recognition Heuristic.
\nKirsten G. Volz, Lael J. Schooler, Ricarda I. Schubotz, Markus Raab, Gerd Gigerenzer, and D. Yves von Cramon<\/p>\n

26. Fluency Heuristic: A Model of How the Mind Exploits a By-Product of Information Retrieval.
\nRalph Hertwig, Stefan M. Herzog, Lael J. Schooler, and Torsten Reimer<\/p>\n

27. The Use of Recognition in Group Decision Making.
\nTorsten Reimer and Konstantinos V. Katsikopoulos<\/p>\n

Part III: Heuristics in the Wild<\/p>\n

Crime<\/p>\n

28. Psychological Models of Professional Decision Making.
\nMandeep K. Dhami<\/p>\n

29. Geographic Profiling: The Fast, Frugal, and Accurate Way.
\nBrent Snook, Paul J. Taylor, and Craig Bennel<\/p>\n

30. Take-the-Best in Expert-Novice Decision Strategies for Residential Burglary.
\nRocio Garcia-Retamero and Mandeep K. Dhami<\/p>\n

Sports<\/p>\n

31. Predicting Wimbledon Tennis Results 2005 by Mere Player Name Recognition.
\nBenjamin Scheibehenne and Arndt Br\u00f6der<\/p>\n

32. Heuristics in Sports That Help Ws Win.
\nW.M. Bennis and Torsten Pachur<\/p>\n

33. How Dogs Navigate to Catch Frisbees.
\nDennis M. Shaffer, Scott M. Krauchunas, Marianna Eddy, and Michael K. McBeath<\/p>\n

Investment<\/p>\n

34. Optimal versus Na\u00efve Diversification: How Inefficient is the 1\/N Portfolio Strategy?
\nVictor DeMiguel, Lorenzo Garlappi, and Raman Uppal<\/p>\n

35. Parental Investment: How an Equity Motive Can Produce Inequality.
\nRalph Hertwig, Jennifer Nerissa Davis, and Frank J. Sulloway<\/p>\n

36. Instant Customer Base analysis: Managerial Heuristics Often “Get It Right.”
\nMarkus W\u00fcbben and Florian v. Wangenheim<\/p>\n

Everyday things<\/p>\n

37. Green Defaults: Information Presentation and Pro-Environmental Behavior.
\nDaniel Pichert and Konstantinois V. Katsikopoulos<\/p>\n

38. “If …”: Satisficing Algorithms for Mapping Conditional Statements onto Social Domains.
\nAlejandro L\u00f3pez-Rousseau and Timothy Ketelaar<\/p>\n

39. Applying One-Reason Decision Making: The Prioritisation of Literature Searches
\nMichael D. Lee, Natasha Loughlin, and Ingrid B. Lundberg<\/p>\n

40. Aggregate Age-at-Marriage Patterns from Individual Mate-Search Heuristics.
\nPeter M. Todd, Francesco C. Billari, and Jorge Sim\u00e3o<\/p>\n","protected":false},"excerpt":{"rendered":"

Gigerenzer, G., Hertwig, R., & Pachur, T. (Eds.). (2011). Heuristics: The Foundations of Adaptive Behavior. New York: Oxford University Press.<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"jetpack_post_was_ever_published":false,"_jetpack_newsletter_access":"","_jetpack_dont_email_post_to_subs":false,"_jetpack_newsletter_tier_id":0,"footnotes":"","jetpack_publicize_message":"","jetpack_publicize_feature_enabled":true,"jetpack_social_post_already_shared":false,"jetpack_social_options":{"image_generator_settings":{"template":"highway","enabled":false}}},"categories":[8,16,2],"tags":[202,20,210,205,208,178,22,203,206,207,36,204,209],"class_list":["post-2497","post","type-post","status-publish","format-standard","hentry","category-books","category-ideas","category-research-news","tag-books-2","tag-decision-making","tag-gerd","tag-gigerenzer","tag-goldstein","tag-hertwig","tag-heuristics","tag-judgment","tag-oxford","tag-pachur","tag-psychology","tag-reader","tag-simple"],"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_shortlink":"https:\/\/wp.me\/p4LKj-Eh","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/www.decisionsciencenews.com\/index.php?rest_route=\/wp\/v2\/posts\/2497","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.decisionsciencenews.com\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.decisionsciencenews.com\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.decisionsciencenews.com\/index.php?rest_route=\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.decisionsciencenews.com\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=2497"}],"version-history":[{"count":11,"href":"https:\/\/www.decisionsciencenews.com\/index.php?rest_route=\/wp\/v2\/posts\/2497\/revisions"}],"predecessor-version":[{"id":2506,"href":"https:\/\/www.decisionsciencenews.com\/index.php?rest_route=\/wp\/v2\/posts\/2497\/revisions\/2506"}],"wp:attachment":[{"href":"https:\/\/www.decisionsciencenews.com\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=2497"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.decisionsciencenews.com\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=2497"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.decisionsciencenews.com\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=2497"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}