demo/replication_li_2010/demo_yahoo_classes/yahoo_policy_random.R

In contextual: Simulation and Analysis of Contextual Multi-Armed Bandit Policies

YahooRandomPolicy <- R6::R6Class(
  portable = FALSE,
  class = FALSE,
  inherit = Policy,
  public = list(
    class_name = "YahooRandomPolicy",
    initialize = function() {
      super$initialize()
    },
    set_parameters = function(context_params) {
      self$theta_to_arms          <- list('n' = 0, 'mean' = 0)
    },
    get_action = function(t, context) {
      action$choice               <- sample(context$arms, 1)
      action
    },
    set_reward = function(t, context, action, reward) {
      arm                         <- action$choice
      reward                      <- reward$reward
      inc(self$theta$n[[arm]])    <- 1
      inc(self$theta$mean[[arm]]) <- (reward - self$theta$mean[[arm]]) / self$theta$n[[arm]]
      self$theta
    }
  )
)