Choose the next alternative(s) to evaluate

Scores every uncertain alternative by the width of its simultaneous confidence box, normalised by the objective ranges and divided by its evaluation cost, and returns the highest-scoring ones. Certified alternatives (dominated or optimal) are never proposed: more evaluations cannot change their certificate. The rule is a heuristic that targets the ambiguous comparisons; it does not affect the validity of the certificates, which holds for any adaptive choice.

Usage

choose_next_evaluation(state, n = 1L)

Arguments

state

A paretoinfer_state.

n

Number of alternatives to propose.

Value

A tibble with columns alternative, score (normalised width per unit cost), width (largest normalised width over objectives) and n_evaluations; zero rows when nothing is uncertain.

Examples

design <- pareto_design(alternatives = 3, objectives = 2, bounds = c(0, 1), epsilon = 0.05)
initialize_pareto(design) |>
  choose_next_evaluation(n = 2)
#> # A tibble: 2 × 4
#>   alternative score width n_evaluations
#>   <chr>       <dbl> <dbl>         <int>
#> 1 A1              1     1             0
#> 2 A2              1     1             0