ALCOVElearning: Attention Learning COVEring map model (ALCOVE)
In mcplR: Multiple Cue Probability Learning in R

Description Usage Arguments Details Value Author(s) References Examples

Constructs the learning submodel of an Attention Learning COVEring map model.

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ALCOVElearning(formula,parameters=list(eta_w=.05,eta_a=.05,r=1,q=1,spf=1),humble=TRUE,
exemplar.locations,data,subset,fixed,parStruct,
random.locations=FALSE,n.locations=10,base=NULL,ntimes,replicate=TRUE)

`formula`	an object of class `formula` (or one that can be coerced to that class): a symbolic description of the model to be fitted. For more details of model speecification, see `lm` or `glm`.
`parameters`	an (optional) list with (starting) values of the parameters. If no values are supplied, defaults are used.
`humble`	logical. If TRUE, humble teaching signal is used.
`exemplar.locations`	(optional) list with exemplar node locations. See details.
`data`	(optional) data frame for evaluation of the formula.
`subset`	(optional) subset of the data.
`fixed`	(optional) logical vector indicating whether parameters are fixed (TRUE) or freely estimable (FALSE).
`parStruct`	(optional) ParStruct object. Note that if parStruct is given, the ‘fixed’ argument above will be ignored.
`random.locations`	If no exemplar.locations are given, should they be determined randomly? If FALSE (default), then unique values of training cues are used as exemplar locations.
`n.locations`	Number of randomly generated exemplar locations, if random.locations = TRUE
`base`	which level of the criterion variable is considered the base category? Defaults to the first level.
`ntimes`	an optional vector with, for each repetition in the data, the total number of trials.
`replicate`	are the repeated series true replications, i.e., are the model parameters considered identical for each series?

ALCOVE (Kruschke, 1992) is based on the GCM model, but has a mechanism to learn the attention weights. It is formulated as an ANN.

A (fitted) object of class ALCOVElearning

Maarten Speekenbrink

Kruschke, J. K. (1992). ALCOVE: An exemplar-based connectionist model of category learning. Psychological Review, 99, 22-44.

## open weather prediction data
data(WPT)
controls <- subset(WPT,id %in% paste("C",1:16,sep=""))
## initialize model
mod <- ALCOVElearning(y~x1+x2+x3+x4,data=controls,
  fix=list(r=TRUE,q=TRUE),ntimes=rep(200,16))
## estimate free parameters (discounting first 5 trials)
## Not run: mod <- fit(mod,discount=5)
summary(mod)