mlr_terminators_genperfreached: Terminator That Stops When a Generation-Wise Aggregated Value...

In miesmuschel: Mixed Integer Evolution Strategies

Terminator That Stops When a Generation-Wise Aggregated Value Reaches a Target

Description

Terminator that terminates when a value, aggregated over generations, reaches a target value.

The user-supplied fitness_aggregator function is called whenever the archive of evaluated configurations contains a new generation. The function is supplied with the fitness values, and optionally other data, of all individuals that are alive at that point (include_previous_generations = FALSE) or at any point (include_previous_generations = TRUE). Its result is saved inside the ⁠$data_extra⁠ field of the Archive object. Termination is then signaled when the aggregated value meets or exceeds level.

The mies_aggregate_single_generation() function is used, see the documentation there for the functioning of fitness_aggregator. The fitness_aggregator functions used for termination must return a scalar value or NULL, if a generation should be ignored. The value returned by fitness_aggregator should be increasing for better performance, even if the underlying objective is being minimized.

Multi-Fidelity Optimization

Multi-fidelity optimization can introduce a few edge-cases because the individuals inside the generation(s) being aggregated may have been evaluated with different fidelity values, which can give biased results.

When OptimizerMies is constructed with multi_fidelity set to TRUE, it typically evaluates some configurations multiple times, at first with a lower fidelity, followed by an evaluation at "full" fidelity. fitness_aggregator will only be called for generations containing entirely full-fidelity-evaluations will be aggregated.

This is achieved by caching aggregated fitness values in the ⁠$data_extra⁠ field of the Archive and only ever calling fitness_aggregator for a generation that does not have a cached value. Since mies_step_fidelity() will count low-fidelity evaluations as part of the "previous" generation, fitness_aggregator will not see them. Note, however that if fitness_aggregator returns NULL, it will be called again should a second evaluation occur in the same generation, since NULL is not cached and instead treated as absent.

It is possible for fitness_aggregator to see fitness values that were evaluated with different fidelities when using OptimizerMies, and

1. fidelity_monotonic is set to TRUE and fidelity decreases (unlikely setup), or

2. if fidelity_current_gen_only is set to FALSE (advanced usage), or

3. The value returned by the fidelity configuration parameter (not fidelity_offspring) changes over the course of optimization and include_previous_generations of TerminatorGenerationStagnation is set to TRUE.

(1) and (2) only need consideration in advanced scenarios, but (3) may be a common, e.g. when doing multi-fidelity optimization and stopping on reaching an overall dominated hypervolume target. In this case, it may be necessary to inspect the budget value given to fitness_aggregator and to remove all individuals evaluated with a different than the current fidelity.

When using a custom-written optimization loop, case (1) relates to fidelity_monotonic argument of mies_step_fidelity() and mies_init_population(), and case (2) relates to the current_gen_only argument of mies_step_fidelity() and the fidelity_new_individuals_only argument of mies_init_population(). Case (3) relates to changing the fidelity given to mies_step_fidelity() if that function is used, or to changing the fidelity given to mies_evaluate_offspring() if mies_step_fidelity() is not used.

Dictionary

This Terminator can be created with the short access form trm() (trms() to get a list), or through the dictionary mlr_terminators in the following way:

# preferred
trm("genperfreached")
trms("genperfreached")  # takes vector IDs, returns list of Terminators

# long form
mlr_terminators$get("genperfreached")

Configuration Parameters

• fitness_aggregator :: function
  Aggregation function, called with information about alive individuals of each generation. This argument is passed to mies_aggregate_single_generation(), see there for more details. The aggregated values returned by fitness_aggregator should be maximized, so a larger value must be returned to indicate improvement in a generation, even if an underlying objective is being minimized. The return value must be a scalar numeric(1).

• include_previous_generations :: logical(1)
  Whether to aggregate over all individuals that were evaluated (TRUE), or only the individuals alive in the current generation (FALSE). If multi-fidelity optimization is being performed and individuals were re-evaluated with a different fidelity, their x_id will be the same and only the last fidelity-reevaluation will be given to fitness_aggregator. However, individuals from different generations may still have been evaluated with different fidelity and it may be necessary to inspect the budget value given to fitness_aggregator if include_previous_generations is TRUE in a multi-fidelity-setting. See the "Multi-Fidelity Optimization" section for more.

• level :: numeric(1)
  Minimum aggregated value for which to terminate.

Super class

bbotk::Terminator -> TerminatorGenerationPerfReached

Methods

Public methods

• TerminatorGenerationPerfReached$new()

• TerminatorGenerationPerfReached$is_terminated()

• TerminatorGenerationPerfReached$clone()

Inherited methods

• bbotk::Terminator$format()
• bbotk::Terminator$print()
• bbotk::Terminator$remaining_time()
• bbotk::Terminator$status()

---

Method new()

Initialize the TerminatorGenerationPerfReached object.

Usage

TerminatorGenerationPerfReached$new()

---

Method is_terminated()

Is TRUE if when the termination criterion is matched, FALSE otherwise.

Usage

TerminatorGenerationPerfReached$is_terminated(archive)

Arguments

archive

Archive Archive to check.

Returns

logical(1): Whether to terminate.

---

Method clone()

The objects of this class are cloneable with this method.

Usage

TerminatorGenerationPerfReached$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.

Examples

set.seed(1)
library("bbotk")
lgr::threshold("warn")

# Terminate when hypervolume with nadir `c(0, 0, ...)`
# does not improve for 3 generations by at least 0.1:
tg <- trm("genperfreached",
  fitness_aggregator = function(fitnesses) domhv(fitnesses),
  include_previous_generations = TRUE,
  level = 1
)

set.seed(1)
objective <- ObjectiveRFun$new(
  fun = function(xs) {
    list(y1 = xs$x1, y2 = xs$x2)
  },
  domain = ps(x1 = p_dbl(0, 1), x2 = p_dbl(-1, 0)),
  codomain = ps(y1 = p_dbl(0, 1, tags = "maximize"),
    y2 = p_dbl(-1, 0, tags = "minimize"))
)

oi <- OptimInstanceMultiCrit$new(objective, terminator = tg)

op <- opt("mies",
  lambda = 4, mu = 4,
  mutator = mut("gauss", sdev = 0.1),
  recombinator = rec("xounif"),
  parent_selector = sel("random"),
  survival_selector = sel("best", scl("hypervolume"))
)

op$optimize(oi)

# the observed aggregated values:
oi$archive$data_extra$TerminatorGenerationPerfReached

# ... or as calculated by mies_generation_apply
mies_generation_apply(oi$archive, function(fitnesses) {
  domhv(fitnesses)
}, include_previous_generations = TRUE)
#' @export

miesmuschel documentation built on April 4, 2025, 5:19 a.m.