Skip to contents

Initialize agents with adaptive and legacy behaviors

initialize_agents.Rd

Assigns behaviors and fitness values to agents in an AgentBasedModel. Can initialize by proportion or fixed count of adaptive agents.

Usage

initialize_agents(
  model,
  initial_prevalence = 0.1,
  adaptive_behavior = "Adaptive",
  adaptive_fitness = 1.2,
  legacy_behavior = "Legacy",
  legacy_fitness = 1
)

Arguments

model

An AgentBasedModel instance.

initial_prevalence

A proportion (0–1) or count of agents starting with the adaptive behavior.

adaptive_behavior

Name of the adaptive behavior (default: "Adaptive").

adaptive_fitness

Fitness value for adaptive behavior (default: 1.2).

legacy_behavior

Name of the legacy behavior (default: "Legacy").

legacy_fitness

Fitness value for legacy behavior (default: 1.0).

Value

Invisibly returns the model with updated agents.

Examples

# Create a model with 20 agents, 25% with adaptive behavior
abm <- 
  make_abm(n_agents = 20) |> initialize_agents(initial_prevalence = 0.25)

# Count how many agents do each behavior
table(purrr::map_chr(abm$agents, ~ .x$get_behavior()))
#> 
#> Adaptive   Legacy 
#>        5       15 

# Summarize fitness values by behavior
tibble::tibble(
  behavior = purrr::map_chr(abm$agents, ~ .x$get_behavior()),
  fitness = purrr::map_dbl(abm$agents, ~ .x$get_fitness())
) |>
  dplyr::group_by(behavior) |>
  dplyr::summarise(count = dplyr::n(), 
                   mean_fitness = mean(fitness), 
                   .groups = "drop")
#> # A tibble: 2 × 3
#>   behavior count mean_fitness
#>   <chr>    <int>        <dbl>
#> 1 Adaptive     5          1.2
#> 2 Legacy      15          1