244App<strong>en</strong>dice I1994). Our stratagem of nested modeling may appear like something leading us close to what Newell (1990)called the "Popperian damnation", i.e. the risk to "kill" theories via falsificationism before one ev<strong>en</strong> has thetime to know their true pot<strong>en</strong>tial. But apart from the fact that Newell's interpretation of Popper's ideas issimply naive and uninformed, we think that nested modeling is a valuable method to tackle this basic problem: By facilitating unification of a single model or family of models, it should also facilitate unificationof competing models. Ev<strong>en</strong> Newell (1990) -not to be suspected to be a "Popperian"- urges cognitive theoreticiansto start by unifying their own theory before attacking a grand unified theory of cognition, which accordingto our view, can only result from strong infer<strong>en</strong>ce competition in a pluralistic, pragmatic but principle-ori<strong>en</strong>tedmodeling perspective. Nested modeling can considerably contribute to that unification.In sum, our bet is that the establishm<strong>en</strong>t of a set of standard criteria for model comparison and evaluationserves this aim of theoretical integration. Since it does not at all exclude parallel anarcho-creative modeling<strong>en</strong>terprises à la Feyerab<strong>en</strong>d (1975), why should we not give it a try 10 ? If we do not solve this problem, thesecond facet of this first chall<strong>en</strong>ge simply risks to remain a chall<strong>en</strong>ge forever!REFERENCESAnderson, J.R. (1990). 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(1976). Adaptive pattern classification and universal recoding. II : Feedback expectation, olfaction,and illusions. Biological Cybernetics , 23, 187-202.Grossberg, S. (1980). How does a brain build a cognitive code. Psychological Review , 87 , 1-51.Grossberg, S., & Stone, G. O. (1986). Neural dynamics of word recognition and recall : att<strong>en</strong>tional priming, learning,and resonance. Psychological Review , 93 , 46-74.Hagège, C. (1986). L'homme de paroles. Paris : Arthème-Fayard.Hooper, D. A., & Paap, K. R. (1996). The use of assembled phonology <strong>du</strong>ring performance of a letter search taskand its dep<strong>en</strong>d<strong>en</strong>ce on the pres<strong>en</strong>ce and proportion of word stimuli. Journal of Memory and Language .Humphreys, M. S., Wiles, J., & D<strong>en</strong>nis, S. (1994). Toward a theory of human memory : Data structures and accessprocesses. Behavioral a nd Brain Sci<strong>en</strong>ces , in press.Jacobs, A. M. (1994). 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Ce travail clôt un cycle de format
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CHAPITRE 7 : LE FUM . . . . . . . .
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8IntroductionPour cela, notre domai
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10Introduction• au niveau lexical
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12Introduction• sa forme visuelle
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14IntroductionAprès avoir posé le
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16Méthodologiespulations sur les i
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18Méthodologies2.1. Protocoles exp
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20Méthodologiessi le stimulus se t
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22MéthodologiesCertaines études t
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24Méthodologiestes, on obtient des
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26Méthodologies1996 ; Peter & Turv
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28Méthodologiesles performances da
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30Méthodologies6 %8%10%15%30%50%80
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32MéthodologiesMatériel expérime
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34Méthodologiesentraîne le masqua
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36MéthodologiesLe même résultat
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38Méthodologies120100Situation Sta
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Chapitre 3Orthographe et phonologie
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42Orthographe et Phonologie3.1. Var
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44Orthographe et PhonologieLa Figur
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46Orthographe et PhonologieJacobs,
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48Orthographe et Phonologiedans la
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50Orthographe et PhonologieDans l
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52Orthographe et Phonologieteurs du
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54Orthographe et PhonologieGoldstei
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56Orthographe et Phonologietion est
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58Orthographe et Phonologierand, 19
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60Orthographe et Phonologieplus ad
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62Orthographe et Phonologie3.2.3.1.
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64Orthographe et PhonologiePlus ré
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66Orthographe et PhonologieUne autr
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68Orthographe et Phonologiedeux var
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Chapitre 4Modèles de la perception
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72Modèles de la perception visuell
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74Modèles de la perception visuell
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76Modèles de la perception visuell
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78Modèles de la perception visuell
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80Modèles de la perception visuell
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82Modèles de la perception visuell
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84Modèles de la perception visuell
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86Modèles de la perception visuell
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88Modèles de la perception visuell
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90Modèles de la perception visuell
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92Modèles de la perception visuell
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94Modèles de la perception visuell
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96Modèles de la perception visuell
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98MROM-pspécifier leur lien avec l
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100MROM-pphonèmes reliés par un r
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102MROM-pLorsque le modèle génèr
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104MROM-pque ce système artificiel
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106Unités de la lecturelinguistiqu
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108Unités de la lecture22606TR (ms
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110Unités de la lecturemes. Aussi
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112Unités de la lecturephonologiqu
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114Unités de la lectureelle-même
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116Unités de la lecture6.3. Expér
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118Unités de la lectureRead est qu
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120Unités de la lectureces modèle
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122Unités de la lecturechapitre su
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124FUMmultiples existant au sein de
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126FUMpar Berndt, Lynne D'Autrechy
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128FUMcessus de compétition et du
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130FUMgène et suit les principes c
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132FUMPseudohomophonesContrôles Or
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134FUM61023TR (ms) Seidenberg et al
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136FUMportementaux et les résultat
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138FUMà une entité extérieure au
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Chapitre 8Des prédictionsau niveau
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142Des prédictions au niveau des m
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144Des prédictions au niveau des m
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146Des prédictions au niveau des m
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150Des prédictions au niveau des m
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160Des prédictions au niveau des m
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162Des prédictions au niveau des m
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164Des prédictions au niveau des m
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166Les mots polysyllabiquesmots mon
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168Les mots polysyllabiquesTableau
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170Les mots polysyllabiques9.2. Exp
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172Les mots polysyllabiques19001890
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174Les mots polysyllabiquesnexe XI
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176Les mots polysyllabiques9.4. Dis
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178ConclusionConclusion« La grande
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180Conclusionplutôt un système o
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182Conclusiontester les prédiction
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184BibliographieAderman, D., & Smit
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186BibliographieBrysbaert, M., Vitu
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188BibliographieFerrand, L., Segui,
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190BibliographieGrainger, J., & Jac
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192BibliographieKay, J., & Bishop,
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- Page 202 and 203: 202AnnexesAnnexes
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- Page 224 and 225: 224Appendice IMROM-P : An interacti
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