BoundedRationality_TheAdaptiveToolbox.pdf

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ations 0 < g < 900. in i ? 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 GW 522 698 734 373 337 51 473 534 561 252 531 205 220 900 518 719 267 854 251 582 642 187 73 236 261 a 36 15 1 36 44 49 48 39 24 33 42 50 35 27 34 6 15 20 49 9 21 17 10 23 40 P 51 40 63 11 64 68 43 11 39 38 66 70 74 30 25 30 27 40 45 33 45 56 54 70 43 | #C 400 375 368 345 268 249 386 401 405 257 388 240 288 410 402 390 255 399 293 387 400 221 66 288 391 #D 1 44 49 47 133 158 5 4 1 102 6 166 113 0 6 5 155 0 99 5 29 156 348 90 5 #C 394 355 357 339 ?67 ?69 379 403 403 268 379 250 291 402 394 375 262 367 292 384 386 251 115 297 393 #D 8 64 60 53 134 138 12 2 3 91 15 156 110 8 14 20 148 32 100 8 43 126 299 81 3 Payoff 152,441 146,235 144,202 142,180 133,808 129,421 154,365 154,992 153,490 129,962 144,805 132,257 139,312 164,423 154,951 148,979 137,977 142,179 132,930 146,649 164,522 126,025 97,982 130,671 151,527 1 1000 1000 270 0 0 0 1000 1000 1000 1000 1000 0 1000 1000 1000 989 915 1000 0 1000 1000 677 0 1000 1000
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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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9 Comparing Fast and Frugal Heurist
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Comparing Fast and Frugal Heuristic
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ComparingFast andFrugal Heuristics
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ation ta emainin Reg = regression,
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174 Daniel G. Goldstein et al envir
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176 Daniel G. Goldstein et al. by r
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178 Daniel G. Goldstein et al What
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180 Daniel G. Goldstein et al secon
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182 Daniel G. Goldstein et al due t
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184 Daniel G. Goldstein et al. term
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186 Daniel G. Goldstein et ah depen
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188 Daniel G. Goldstein et al. aver
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190 Daniel G. Goldstein et al. Hoga
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192 Daniel M. T. Fessler and comple
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194 Daniel M.T. Fessler SHAME AND R
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196 Daniel M. T. Fessler and 3. As
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198 Daniel M. T. Fessler In many pr
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200 Daniel M. T. Fessler (i.e., "bl
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202 Daniel M. T. Fessler collaborat
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204 Daniel M. T. Fessler talents. N
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206 Daniel M. T. Fessler this syste
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208 Daniel M. T. Fessler The powerf
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210 Daniel M. T. Fessler 4 Througho
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Daniel M. T. Fessler rect. The auth
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214 Daniel M. T. Fessler Lerner, J.
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216 Ido Erev andAlvin E. Roth adjus
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218 game/ choice prob. S&A2: A2 B2
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220 Ido Erev andAlvin E. Roth \ ('+
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222 Sequential Effects Ido Erev and
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224 Ido Erev andAlvin E. Roth and 1
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226 Ido Erev andAlvin E. Roth The f
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228 Ido Erev andAlvin E. Roth C cho
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230 Ido Erev andAlvin E. Roth behav
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13 Imitation, Social Learning, and
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Imitation, Social Learning, and Pre
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250 Thomas D. Seeley workers) have
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252 Thomas D. Seeley group — be c
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254 Thomas D. Seeley ceased to danc
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256 Thomas D. Seeley scout bees wer
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258 Thomas D. Seeley ceased their d
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260 Thomas D. Seeley operates with
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NL r*;- Seated, left to right: Ido
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264 Barbara A. Mellers et al Darwin
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266 Barbara A. Mellers et al (Mesqu
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268 Barbara A. Mellers et al test s
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270 Barbara A. Mellers et ah decisi
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272 Barbara A. Mellers et ah Imitat
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274 Barbara A. Mellers et al. more
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276 Barbara A. Metiers et al REFERE
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278 Barbara A. Mellers et al Loewen
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16 Norms and Bounded Rationality Ro
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Norms and Bounded Rationality 283 g
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Probability Density of X Norms and
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Norms and Bounded Rationality 287 E
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3 Va E 3 J— lib 3 LU 1 0.9 0.8 0.
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Norms and Bounded Rationality 291 e
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m/a Norms and Bounded Rationality 2
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Norms and Bounded Rationality 295 f
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17 Prominence Theory as a Tool to M
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Prominence Theory 299 constructs he
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Prominence Theory 301 The presentat
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Prominence Theory 303 cruder relati
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Prominence Theory 305 frequency. We
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Prominence Theory 307 90%, 100%o, i
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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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