func_zeta: Function: Decay Rate

In multiRL: Reinforcement Learning Tools for Multi-Armed Bandit

Function: Decay Rate

Description

W_{new} = W_{old} + \zeta \cdot (W_{0} - W_{old})

Usage

func_zeta(
  shown,
  is.nb,
  value0,
  values,
  reward,
  utility,
  system,
  rownum,
  params,
  hidden,
  ...
)

Arguments

shown	Which options shown in this trial.
is.nb	Is it the new block?
value0	The initial values for all actions.
values	The current expected values for all actions.
reward	The feedback received by the agent from the environment at trial(t) following the execution of action(a)
utility	The subjective value (internal representation) assigned by the agent to the objective reward.
system	When the agent makes a decision, is a single system at work, or are multiple systems involved? see system
rownum	The trial number
params	Parameters used by the model's internal functions, see params
hidden	All hidden variables within the MDP process belong here.
...	It currently contains the following information; additional information may be added in future package versions. idinfo: subid block trial exinfo: contains information whose column names are specified by the user. Frame RT NetWorth ... behave: includes the following: action: the behavior performed by the human in the given trial. latent: the object updated by the agent in the given trial. simulation: the actual behavior performed by the agent. position: the position of the stimulus on the screen. cue and rsp: Cues and responses within latent learning rules, see behrule state: The state stores the stimuli shown in the current trial—split into components by underscores—and the rewards associated with them.

Value

A List

• output [NumericVector]

  The values of unchosen options after decay according to the specified decay rate.

• hidden [CharacterVector]

  User-defined internal variables generated by this function. These represent intermediate (latent) states produced during computation, which can be read or modified by other functions in the MDP process.

Body

func_zeta <- function(
    shown,
    value0, 
    values,
    reward,
    utility,
    system,
    rownum,
    params,
    hidden,
    ...
){

  list2env(list(...), envir = environment())
  
  # If you need extra information(...)
  # Column names may be lost(C++), indexes are recommended
  # e.g.
  # Trial  <- idinfo[3]
  # Frame  <- exinfo[1]
  # Action <- behave[1]
  
  zeta       <-  params[["zeta"]]
  bonus      <-  params[["bonus"]]
  reset      <-  params[["reset"]]
    
  # If reset all Q values 
  if (is.nb && !is.na(reset)) {
    decay <- rep(reset, length(values))
    hidden[6] <- "reset"
    return(list(output = decay, hidden = hidden)) 
  } 

  if (reward == 0) {
    decay <- values + zeta * (value0 - values)
  } else if (reward < 0) {
    decay <- values + zeta * (value0 - values) + bonus
  } else if (reward > 0) {
    decay <- values + zeta * (value0 - values) - bonus
  }
  
  return(list(output = decay, hidden = hidden)) 
}

multiRL documentation built on June 9, 2026, 5:09 p.m.