Cognitive Science models repository

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Contents

Basic models

-Coin flipping (randomness and coincidence detection).

-Representativeness.

-Predicting the future.

-The number game.


Categorization

-Prototype and exemplar models: mixture models.

-Property-based induction.

-Fancy categorization: IRM, CrossCat, etc.

-Rule-based models (grammar-based induction).


Function learning

-Bayesian regression.


Causality

-Bayes nets.

-Elemental causal induction: delta-P, power-PC, causal support.

-Time (nitro-X, Tevye...)

-Causal schemata.

-Grounded causal models.


Overhypotheses

-Bags-o-marbles.

-Word learning (shape bias).

-Framework theories for curve fitting.

-Structural forms for property induction.

-Causal schemata.


Language

-PCFG

-Cross-situational word learning.

-CCG?


Decision making and Planning

Social cognition

-Goal inference.

-Preference learning.

-Belief stuff.

-Morality (qua game theory).


Objects

Vision

-Brightness constancy.

-Surface perception: texture/shading.

-Cue combination, perceptual explaining away.

-Grouping principles.


Interactions

Data analysis

Personal tools