-- Define the genetic algorithm parameters
local population_size = 10
local mutation_rate = 0.1
local generations = 100
-- Define the initial map and player position
local map = { width = 100, height = 100 }
local player_position = { x = 10, y = 10 }
-- Define the initial population of characters
local population = {}
for i = 1, population_size do
table.insert(population, {
position = { x = 1, y = 1 },
destination = { x = math.random(map.width), y = math.random(map.height) },
move_speed = 2 + math.random() * 2,
has_health = false,
has_armor = false,
has_weapon = false,
has_ammo = false,
is_attacking = false,
fitness = 0
})
end
-- Define the behaviors for picking up items and attacking the player
function pickup_item(character, item_type)
-- Define the behavior for picking up items
end
function attack_player(character)
-- Define the behavior for attacking the player
end
-- Define the main behavior loop for each character in the population
function update(character)
-- Move towards the destination
local dx = character.destination.x - character.position.x
local dy = character.destination.y - character.position.y
local distance = math.sqrt(dx * dx + dy * dy)
local speed = character.move_speed
if distance < speed then
character.position.x = character.destination.x
character.position.y = character.destination.y
character.destination.x = math.random(map.width)
character.destination.y = math.random(map.height)
else
character.position.x = character.position.x + dx / distance * speed
character.position.y = character.position.y + dy / distance * speed
end
-- Check for items to pick up
-- ...
-- Check if the player is nearby and attack if so
-- ...
-- Check if the character failed (e.g. health = 0) and reset if so
if character.has_health and character.has_health <= 0 then
character.position.x = 1
character.position.y = 1
character.destination.x = math.random(map.width)
character.destination.y = math.random(map.height)
character.has_health = false
character.has_armor = false
character.has_weapon = false
character.has_ammo = false
character.is_attacking = false
character.fitness = 0
end
end
-- Define the fitness function for each character
function evaluate_fitness(character)
-- Evaluate the character's fitness based on its performance
local fitness = 0
if character.has_weapon and character.is_attacking then
fitness = fitness + 1
end
if character.has_armor then
fitness = fitness + 1
end
if character.has_health then
fitness = fitness + 1
end
return fitness
end
-- Implement the genetic algorithm loop
for generation = 1, generations do
-- Evaluate the fitness of each character in the population
for i = 1, population_size do
local character = population[i]
evaluate_fitness(character)
end
-- Sort the population by fitness
table.sort(population, function(a, b)
return a.fitness > b.fitness
end)
-- Select the fittest characters to reproduce
local selected = {}
for i = 1, math.floor(population_size / 2) do