## From Learning Theory to Connectionist TheoryAlice F. Healy, Stephen Michael Kosslyn, Richard M. Shiffrin These two volumes consist of chapters written by students and colleagues of W.K. Estes. The books' contributors -- themselves eminent figures in the field -- reflect on Estes' sweeping contributions to mathematical as well as cognitive and experimental psychology. As indicated by their titles, Volume I features mathematical and theoretical essays, and Volume II presents cognitive and experimental essays. Both volumes contain insightful literature reviews as well as descriptions of exciting new theoretical and empirical advances. Many of the essays also incorporate personal reminiscences reflecting the authors' fond affection for their illustrious mentor. |

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### Contents

Estes Statistical Learning Theory Past Present and Future | 1 |

Choosing Between Uncertain Options A Reprise to the Estes Scanning Model | 21 |

A Path Taken Aspects of Modern Measurement Theory | 45 |

Chaos Theory A Brief Tutorial and Discussion | 65 |

Imitatio Estes Stimulus Sampling Origins of Webers Law | 97 |

A Mathematical Theory of Attention in a Distractor Task | 115 |

Triple Correlation and Texture Discrimination | 133 |

Exemplars Prototypes and Similarity Rules | 149 |

Stimulus Sampling and Distributed Representations in Adaptive Network Theories of Learning | 169 |

Serial Organization in a Distributed Memory Model | 201 |

Reducing Interference in Distributed Memories Through Episodic Gating | 227 |

What Good is Connectionist Modeling? A Dialogue | 249 |

267 | |

275 | |

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### Common terms and phrases

activations adaptive network associated autocorrelation function behavior binary Cantor set chaos chaos theory chaotic choice chunk cognitive connectionism connectionist context model cues denote dimension discrimination display distributed dynamics effect episodic units Equation error example exemplar models expected utility Experimental Psychology experiments finite flanker Gluck hidden units interference item vectors Journal of Experimental Julesz KOSSLYN LaBerge linear Luce mapping Mathematical Psychology measurement Medin memory micropatterns MSP model multiple convolutions multiplicative-similarity n-grams network model output unit pairs Parallel distributed processing parameter patterns Poisson predictions presented probability processes proportions prototype model Psychological Review random recall reinforcement representation Rescorla-Wagner model retrieval retroactive interference RUECKL Rumelhart scanning model Science second-order statistics similarity statistical learning theory stimulus elements Stimulus Sampling Theory stochastic structure subjects Suppes target texture third-order statistics tion trajectory trial triple correlation variables Weber's Weber's Law weights Willshaw Willshaw network zero