rescorla_wagner: Rescorla-Wagner (1972) error-driven associative model

In XSLmodels: Run and Optimize Cross-Situational Word Learning Models

Rescorla-Wagner (1972) error-driven associative model

Description

Rescorla-Wagner (1972) error-driven associative model

Usage

rescorla_wagner(C, alpha, beta, lambda)

Arguments

C	Decay
alpha	Salience (fix at 1 unless manipulated)
beta	Learning rate – a proportion of lambda
lambda	Maximum associative value that a CS can achieve - should be larger than learning rate

Value

An object of class xslMod

Examples

mod <- rescorla_wagner(C = 1, alpha = 1, beta = 0.1, lambda = 3)
xsl_run(mod, get_example_ambiguous_condition())

XSLmodels documentation built on Oct. 18, 2026, 5:08 p.m.