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BoundedRationality_TheAdaptiveToolbox.pdf

BoundedRationality_TheAdaptiveToolbox.pdf

  • Page 2: February 2001 ISBN 0-262-07214-9 37
  • Page 6: 2 Gerd Gigerenzer andReinhard Selte
  • Page 10: 4 Gerd Gigerenzer andReinhard Selte
  • Page 14: 6 Gerd Gigerenzer and Reinhard Selt
  • Page 18: 8 Gerd Gigerenzer and Reinhard Selt
  • Page 22: 10 Gerd Gigerenzer and Reinhard Sel
  • Page 26: 12 Gerd Gigerenzer and Reinhard Sel
  • Page 30: 14 Reinhard Selten decision alterna
  • Page 34: 16 Reinhard Selten only an optimal
  • Page 38: 18 Reinhard Selten ASPIRATION ADAPT
  • Page 42: 20 Reinhard Selten The process may
  • Page 46: 22 Reinhard Selten last period's va
  • Page 50: 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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    126 John W. Payne and James R. Bett

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    128 John W. Payne and James R. Bett

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    130 John W. Payne and James R. Bett

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    132 John W. Payne and James R. Bett

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    134 John W. Payne and James R. Bett

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    136 John W. Payne and James R. Bett

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    138 John W. Payne and James R. Bett

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    140 John W. Payne and James R. Bett

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    142 John W. Payne and James R. Bett

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    144 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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    Comparing Fast and Frugal Heuristic

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    ComparingFast andFrugal Heuristics

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    Comparing Fast and Frugal Heuristic

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    Comparing Fast and Frugal Heuristic

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    Comparing Fast and Frugal Heuristic

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    Comparing Fast and Frugal Heuristic

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    Comparing Fast and Frugal Heuristic

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    Comparing Fast and Frugal Heuristic

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    ation ta emainin Reg = regression,

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    Comparing Fast and Frugal Heuristic

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    Comparing Fast and Frugal Heuristic

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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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    Imitation, Social Learning, and Pre

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    Imitation, Social Learning, and Pre

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    Imitation, Social Learning, and Pre

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    Imitation, Social Learning, and Pre

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    Imitation, Social Learning, and Pre

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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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    Prominence Theory 309 equal relativ

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    Prominence Theory 311 of 200. The p

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    Prominence Theory 313 could decide

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    Prominence Theory 315 (6) a stronge

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    Prominence Theory 317 P.M. Todd, an

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    320 Kevin A. McCabe and Vernon L. S

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    322 Kevin A. McCabe and Vernon L. S

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    324 Kevin A. McCabe and Vernon L. S

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    326 Kevin A. McCabe and Vernon L. S

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    328 Kevin A. McCabe and Vernon L. S

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    330 Kevin A. McCabe and Vernon L. S

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    332 Kevin A. McCabe and Vernon L. S

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    ations 0 < g < 900. in i ? 3 4 5 6

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    Goodwill Accounting and the Process

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    Goodwill A ccoun ting and the Proce

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    ^1 §# ; Standing, left to right: P

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    344 Joseph Henrich et al. behaviora

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    346 Joseph Henrich et al copiers as

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    348 Joseph Henrich et ah and cooper

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    350 Joseph Henrich et al. (so relia

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    352 Joseph Henrich et al then this

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    354 Joseph Henrich et al. explain t

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    356 Joseph Henrich et al. continue

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    358 Joseph Henrich et ah REFERENCES

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    abundant information 157, 158, 188

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    decision making continued ignorance

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    fitting 59, 60, 78, 148, 150, 152,

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    linear models 45,47, 155, 156, 168,

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    social learning continued definitio

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    List of Participants W. ALBERS Inst

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    List of Participants with Fields of

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    List of Participants with Fields of

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    372 Byrne, R.W. 53 Caldecott, J.O.

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    374 Jolls, C. 6, 37 Kacelnik,A. 173

  • Page 728:

    376 Name Index Schmitt,M. 152-154,

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