BoundedRationality_TheAdaptiveToolbox.pdf

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ation ta emainin Reg = regression, NB = Naive Bayes, BN = Bayesian network (Martignon and Laske Environment Ozone in San Francisco Cow manure Oxidant Mortality House price Rainfall Biodiversity Attractiveness of women Attractiveness of men Mammals' sleep Car accidents Obesity at age 18 Fuel consumption Homelessness Professors' salaries High school dropout rates Land rent City population Body fat Fish fertility Average over the 20 data sets # Objects 11 14 17 20 22 24 26 30 32 35 37 46 48 50 51 57 58 83 218 395 #Cues 3 6 4 15 10 6 6 3 3 9 13 10 6 6 1 5 18 4 9 14 3 PM 85 83 93 100 96 71 88 80 75 95 93 70 87 82 87 90 82 80 87 75 85 TTB 84 79 84 77 86 67 84 71 73 78 71 74 78 69 80 65 80 74 59 73 75 Fitting Reg 85 79 84 83 86 71 80 71 73 79 79 74 79 70 83 72 81 74 61 75 77
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February 2001 ISBN 0-262-07214-9 37
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2 Gerd Gigerenzer andReinhard Selte
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4 Gerd Gigerenzer andReinhard Selte
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6 Gerd Gigerenzer and Reinhard Selt
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8 Gerd Gigerenzer and Reinhard Selt
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10 Gerd Gigerenzer and Reinhard Sel
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12 Gerd Gigerenzer and Reinhard Sel
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14 Reinhard Selten decision alterna
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16 Reinhard Selten only an optimal
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18 Reinhard Selten ASPIRATION ADAPT
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20 Reinhard Selten The process may
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22 Reinhard Selten last period's va
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24 Reinhard Selten 2. local procedu
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26 Reinhard Selten whether the town
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28 Reinhard Selten The term ex post
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30 Reinhard Selten Human Problem So
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32 Reinhard Selten indirect influen
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34 Reinhard Selten Want Generator a
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36 Reinhard Selten Holland, J., K.
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38 Gerd Gigerenzer The notion of an
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40 Gerd Gigerenzer the psychologist
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42 Gerd Gigerenzer consider two com
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44 Gerd Gigerenzer (Simon 1955). Cu
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46 Gerd Gigerenzer Incommensurabili
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48 Gerd Gigerenzer To summarize, th
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50 Gerd Gigerenzer Selten, R. 1998.
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52 Peter M. Todd for which our mind
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54 Peter M. Todd behavior, as explo
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56 Peter M. Todd make a categorical
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58 Peter M. Todd One-reason Decisio
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60 Peter M. Todd Table 4.1 Performa
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62 Peter M. Todd Such distributions
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64 Peter M. Todd analysis of the re
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66 Peter M. Todd The early limitati
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68 Peter M. Todd within which heuri
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70 Peter M. Todd Luria, A.R. 1968.
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72 Peter Hammerstein Biologist: Let
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74 Peter Hammerstein organism throu
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76 Peter Hammerstein a' =a + 5/(^+1
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78 Peter Hammerstein Biologist: Wel
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80 Peter Hammerstein These are part
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Seated left to right: Bertrand Muni
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84 Abdolkarim Sadrieh et al. issue
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86 Abdolkarim Sadrieh et al. Using
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88 Abdolkarim Sadrieh et al Most im
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90 Abdolkarim Sadrieh et al arbitra
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92 Abdolkarim Sadrieh et al. with t
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94 Abdolkarim Sadrieh et al. search
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96 Abdolkarim Sadrieh et al. Divers
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98 Abdolkarim Sadrieh et al Dichoto
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100 Abdolkarim Sadrieh et al. imple
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102 Abdolkarim Sadrieh et ah Moxnes
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104 Gary Klein stem from limited co
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106 Gary Klein action were undertak
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108 Gary Klein optimization as find
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110 Gary Klein reasonable level. Th
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112 Gary Klein selecting the best o
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124 John W. Payne and James R. Bett
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Page 262: 140 John W. Payne and James R. Bett
Page 274: 9 Comparing Fast and Frugal Heurist
Page 278: Comparing Fast and Frugal Heuristic
Page 286: ComparingFast andFrugal Heuristics
Page 316: 168 Laura Martignon inherent struct
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Page 328: Why and When Do Simple Heuristics W
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Emotions and Cost-benefit Assessmen
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12 Simple Reinforcement Learning Mo
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Reinforcement Learning and Reciproc
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234 Kevin N. Laland observation of
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236 Kevin N. Laland transmission (L
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238 Kevin N. Laland example, reflec
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240 Kevin N. Laland the social tran
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242 Kevin N. Laland example, bats t
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244 Kevin N. Laland A focus on soci
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246 Kevin N. Laland Durham, W.H. 19
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14 Decision Making in Superorganism
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Decision Making in Superorganisms 2
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11:00-13:00 bees: 18 dances: 68 wag
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15 Group Report: Effects of Emotion
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Effects of Emotions and Social Proc
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282 Robert Boyd and Peter J. Richer
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298 WulfAlbers consecutive full-ste
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300 WulfAlbers and must decide betw
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302 WulfAlbers and only if their di
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304 WulfAlbers considered. Thus, th
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306 WulfAlbers S(r, a) can contain
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308 WulfAlbers however, it also has
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310 WulfAlters utility function, pr
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312 WulfAlbers AGGREGATION OF UTILI
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314 WulfAlters Nash problem with co
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316 WulfAlbers concession steps in
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18 Goodwill Accounting and the Proc
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Goodwill Accounting and the Process
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Environment Information w Personal
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334 Kevin A. McCabe and Vernon L. S
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able 18.3 200 iterations < g < 900.
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19 Group Report: What Is the Role o
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What Is the Role of Culture in Boun
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362 Subject Index Bayesian rational
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364 Subject Index environment conti
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366 Subject Index hill-climbing alg
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368 Subject Index probability 3, 6,
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370 value continued estimation of c
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xii List of Participants with Field
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xiv List of Participants with Field
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Abbink, K. 29 Abdellaoui, M. 92 Ain
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Frisch, D. 104, 127, 134 Gagne,R.M.
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Mitchell, T.R. 130 Mookerjee, D. 21
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Name Index 317 Wong, C. 206 Zajonc,
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