Why is the Rescorla-Wagner model so influential?

被引:7
作者
Soto, Fabian A. [1 ]
Vogel, Edgar H. [2 ,3 ]
Uribe-Bahamonde, Yerco E. [4 ]
Perez, Omar D. [5 ,6 ]
机构
[1] Florida Int Univ, Miami, FL 33199 USA
[2] Univ Talca, Fac Psychol, Res Ctr Cognit Sci, Talca, Chile
[3] Univ Talca, Fac Psychol, Appl Psychol Ctr, Talca, Chile
[4] Univ Talca, Talca, Chile
[5] Univ Chile, Dept Ind Engn, Santiago, Chile
[6] Inst Sistemas Complejos Ingn, Santiago, Chile
关键词
Rescorla-Wagner; Prediction error; Learning rules; Computational; Pavlovian conditioning; Reinforcement; Supervised learning; Learning algorithm; CUE COMPETITION; STIMULUS-GENERALIZATION; OBJECT CATEGORIZATION; PREDICTION ERRORS; CAUSAL POWER; BLOCKING; CONTINGENCY; EXPECTATION; ACQUISITION; EXTINCTION;
D O I
10.1016/j.nlm.2023.107794
中图分类号
B84 [心理学]; C [社会科学总论]; Q98 [人类学];
学科分类号
03 ; 0303 ; 030303 ; 04 ; 0402 ;
摘要
The influence of the Rescorla-Wagner model cannot be overestimated, despite that (1) the model does not differ much computationally from its predecessors and competitors, and (2) its shortcomings are well-known in the learning community. Here we discuss the reasons behind its widespread influence in the cognitive and neural sciences, and argue that it is the constant search for general-process theories by learning scholars which eventually produced a model whose application spans many different areas of research to this day. We focus on the theoretical and empirical background of the model, the theoretical connections that it has with later developments across Marr's levels of analysis, as well as the broad variety of research that it has guided and inspired.
引用
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页数:11
相关论文
共 137 条
  • [1] Allan LG, 2003, LEARN BEHAV, V31, P192
  • [2] Anderson J. R., 1990, The adaptive character of thought
  • [3] [Anonymous], 1990, Learning and computational neuroscience: Foundations of adaptive networks
  • [4] [Anonymous], 1963, HDB MATH PSYCHOL
  • [5] Words from spontaneous conversational speech can be recognized with human-like accuracy by an error-driven learning algorithm that discriminates between meanings straight from smart acoustic features, bypassing the phoneme as recognition unit
    Arnold, Denis
    Tomaschek, Fabian
    Sering, Konstantin
    Lopez, Florence
    Baayen, R. Harald
    [J]. PLOS ONE, 2017, 12 (04):
  • [6] An Amorphous Model for Morphological Processing in Visual Comprehension Based on Naive Discriminative Learning
    Baayen, R. Harald
    Milin, Petar
    Durdevic, Dusica Filipovic
    Hendrix, Peter
    Marelli, Marco
    [J]. PSYCHOLOGICAL REVIEW, 2011, 118 (03) : 438 - 481
  • [7] CONDITIONED INHIBITION IS NOT SYMMETRICAL OPPOSITE OF CONDITIONED EXCITATION - TEST OF RESCORLA-WAGNER MODEL
    BAKER, AG
    [J]. LEARNING AND MOTIVATION, 1974, 5 (03) : 369 - 379
  • [8] PROPERTIES OF COMPOUND CONDITIONED STIMULI AND THEIR COMPONENTS
    BAKER, TW
    [J]. PSYCHOLOGICAL BULLETIN, 1968, 70 (6P1) : 611 - +
  • [9] Investigating Cue Competition in Contextual Cuing of Visual Search
    Beesley, T.
    Shanks, David R.
    [J]. JOURNAL OF EXPERIMENTAL PSYCHOLOGY-LEARNING MEMORY AND COGNITION, 2012, 38 (03) : 709 - 725
  • [10] Bitterman M.E., 2000, The evolution of cognition, P61