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#' Eligibility traces
#'
#' Eligibility traces.
#'
#' Algorithms supporting eligibility traces:
#' * [QLearning]
#'
#' @param lambda \[`numeric(1)` in (0, 1)] \cr Trace decay parameter.
#' @param traces \[`character(1)`] \cr Type of eligibility trace update. One of `c("replace", "accumulate")`.
#'
#' @name Eligibility
#' @md
#'
#' @aliases eligibility
#'
#' @examples
#' alg = makeAlgorithm("qlearning", lambda = 0.8, traces = "accumulate")
NULL
Eligibility = R6::R6Class("Eligibility",
public = list(
lambda = 0,
eligibility.type = NULL,
E = NULL,
initialize = function(lambda = 0, traces = "accumulate") {
self$lambda = lambda
if (traces == "replace") {
self$eligibility.type = 1
} else if (traces == "accumulate") {
self$eligibility.type = 0
}
},
reset = function(val.fun) {
self$E = matrix(0, nrow = nrow(val.fun), ncol = ncol(val.fun))
},
increase = function(s, a) {
self$E[s + 1L, a + 1L] = (1 - self$eligibility.type) * self$E[s + 1L, a + 1L] + 1
},
decrease = function(discount) {
self$E = discount * self$lambda * self$E # sarsa
}
)
)
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