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neat.lua
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neat.lua
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--===========================================================================--
---------------------------NEAT algorithm for MK64-----------------------------
--===========================================================================--
-- --
-- Author: Nick Nelson --
-- November, 2016 --
-- You may freely use this code, but please give credit to the original --
-- author. --
-- --
-- Setup: create a save state at the beginning of a level. Call it
-- LR150.state and save it in the lua folder. Note: So far I have only
-- tested this on Luigi Raceway with 150cc.
--===========================================================================--
--[[
Known bugs:
- replay best, then reload, in_cell is now nil. update: this only happens
sometimes, just do it again
Possible bugs:
- in at least one case a single species took over the entire population, which
could mean i have something wrong in the code that is supposed to prevent
this...
Haven't tested:
- load a backup file instead of the saved file
- spawning code could use more testing
Areas for improvement:
- adjust mutation code to better suit the problem
Some unknown object types:
- 43 hot air balloon in luigi raceway?
- 42 blue shell I think
- 21 dead banana?
- 22 dead banana?
- 14
]]
function p(line)
console.write(line)
end
function pn(line)
console.writeline(line)
end
function initialize_things()
console.clear()
-- pn(game)
pn('MK64 NEAT')
state_file = "BB150.state"
-- TODO add bumpers?
button_input_names = {
-- "Start",
"P1 B",
"P1 A",
"P1 Z",
"P1 A Down",
"P1 A Left",
"P1 A Right",
"P1 A Up",
"P1 L",
"P1 R" }
button_actual_names = {
-- "Start",
"B",
"A",
"Z",
"Down",
"Left",
"Right",
"Up",
"L",
"R" }
num_buttons = #button_actual_names
course = {}
-- collision address
course.col_addresses = {
0x1D65A0, -- Mario Raceway
0x1D4280, -- Choco Mountain
"",
0x1D8380, -- Banshee Boardwalk
0x1E5170, -- Yoshi Valley
0x1D4650, -- Frappe Snowland
0x1E6380, -- Koopa Troopa Beach
0x1DAF50, -- Royal Raceway
0x1DD1C0, -- Luigi Raceway
0x1E1500, -- Moo Moo Farm
0x1F0AC0, -- Toad's Turnpike
0x1F0120, -- Kalamari Desert
0x1D6A70, -- Sherbet Land
0x1E3080, -- Rainbow Road
0x1D9AE0, -- Wario Stadium
"",
"",
"",
0x1E1300,
""} --
-- the collision attribute for each track
course.track_attribute = {
"", -- Mario Raceway
"", -- Choco Mountain
"",
6,
2, -- Yoshi Valley
5, -- Frappe Snowland
3, -- Koopa Troopa Beach
1, -- Royal Raceway
1, -- Luigi Raceway
2, -- Moo Moo Farm
1, -- Toad's Turnpike
2, -- Kalamari Desert
"", -- Sherbet Land
1, -- Rainbow Road
"", -- Wario Stadium
"",
"",
"",
2,
""}
course.names = {
"Mario Raceway ",
"Choco Mountain ",
"Bowser's Castle ",
"Banshee Boardwalk ",
"Yoshi Valley ",
"Frappe Snowland ",
"Koopa Troopa Beach ",
"Royal Raceway ",
"Luigi Raceway ",
"Moo Moo Farm ",
"Toad's Turnpike ",
"Kalimari Desert ",
"Sherbet Land ",
"Rainbow Road ",
"Wario Stadium ",
"Block Fort ",
"Skyscraper ",
"Double Deck ",
"DK's Jungle Parkway",
"Big Donut "}
savestate.load(state_file)
course.selected_addr = 0xDC5A0
course.number = mainmemory.read_u16_be(course.selected_addr) + 1
course.name = course.names[course.number]
course.col_start = course.col_addresses[course.number]
-- course.col_fin = course.col_addr_fins[course.number]
course.col_step = 0x2C
course.col_attr_offset = 0x02
course.p1_offset = 0x11
course.p2_offset = 0x15
course.p3_offset = 0x19
course.tr_attr = course.track_attribute[course.number]
-- this loads the map, just the track sections though
load_map()
-- kart data
kart = {}
kart.x_addr = 0x0F69A4
kart.xv_addr = 0x0F69C4
kart.y_addr = 0xF69A8
kart.yv_addr = 0x0F69C8
kart.z_addr = 0x0F69AC
kart.zv_addr = 0x0F69CC
dist_addr = 0x16328A
kart.sin = 0xF6B04
kart.cos = 0xF6B0C
character_addr = 0x0DC53B
character = mainmemory.read_u8(character_addr)
-- object addresses
obj = {}
obj.addr = 0x15F9B8
obj.stop = 0x162578
obj.step = 0x70
obj.x_offset = 0x18
obj.y_offset = 0x1C
obj.z_offset = 0x20
-- some colors
black = 0xFF000000
white = 0xFFFFFFFF
red = 0xFFFF0000
bred = 0x60FF0000
green = 0xFF00FF00
sgreen = 0xFF009900
blue = 0xFF0000FF
yellow = 0xFFFFFF00
fbox = 0xFF00007F
bblue = 0x200000FF
l_off = 0x500000FF
bwhite = 0x60FFFFFF
back = 0x40808080
none = 0x00000000
b_on = 0xFF1d2dc1
b_off = 0x90000000
player = {
0x80FF0000, -- mario
0x0, -- luigi
0x0, --
0x0, --
0x0, --
0x0, --
0x0, --
0x0} --
math.randomseed(os.time())
box_radius = 6
num_inputs = box_radius*box_radius*4
max_nodes = 1000000
fitness = 0
gain = 0
highest_fitness = 0
highest_distance = 0
global_max_fitness = 0
global_best_genome = new_genome()
replay_best_genome = false
not_advanced = 20
global_innovation = 0
current_species = 0
population = 200
compatibility_threshold = 1.0
c1 = 1
c2 = 1
c3 = 1
mutate_weights_chance = 0.25
weight_perturbation = 2
-- must be at least one so all genomes have at least one gene
mutate_structure_chance = 1
add_node_chance = 0.66
clear_controller()
-- initialize population
initialize_population()
end -- end initialize_things
function create_form()
form = forms.newform(250, 400, "MK64 NEAT")
hide_net = forms.checkbox(form, "Hide Network", 5, 5)
hide_xyz_data = forms.checkbox(form, "Hide Info", 5, 25)
load_save_label = forms.label(form, "Save/Load file:", 5, 50)
load_save_backup = forms.textbox(
form, state_file.."_frequent_backup.txt", 155, 30, nil, 5, 73
)
-- see next_genome() function
save_button = forms.button(form, "Save", save_here, 5, 95)
load_button = forms.button(form, "Load", load_generation, 85, 95)
replay_best_button = forms.button(
form, "Replay Best", replay_best, 5, 125
)
restart_button = forms.button(form, "Restart", initialize_things, 85, 125)
l_generation = forms.label(form, "Generation: 0", 5, 160)
l_species = forms.label(form, "Species: 0", 5, 185)
l_genome = forms.label(form, "Genome: 0", 5, 210)
l_fitness = forms.label(form, "Fitness: 0", 5, 235)
l_max_fitness = forms.label(form, "Max Fitness: 0", 5, 260)
l_member = forms.label(form, "Member: ", 5, 285)
end
function game_over()
forms.destroy(form)
end
function round(num, idp)
local mult = 10^(idp or 0)
return math.floor(num * mult + 0.5) / mult
end
function display_info()
gui.drawBox(-1, 214, 320, 240, none, bwhite)
-- gui.drawText(-2, 212, course.name, black, none)
gui.drawText(-2, 212, "Generation:"..pop.generation, black, none)
gui.drawText(120, 212, "Species:"..pop.current_species, black, none)
gui.drawText(240, 212, "Genome:"..pop.current_genome, black, none)
gui.drawText(-1, 224, "Fitness:".. round(fitness), black, none)
gui.drawText(
90, 224, "Max Fitness:"..round(global_max_fitness), black, none
)
gui.drawText(215, 224, "Member:"..pop.member.."/"..population, black, none)
if pop.frame_count % 10 == 0 then
forms.settext(l_generation, "Generation: "..pop.generation)
forms.settext(l_species, "Species: "..pop.current_species)
forms.settext(l_genome, "Genome: "..pop.current_genome)
forms.settext(l_fitness, "Fitness: "..round(fitness))
forms.settext(l_max_fitness, "Max Fitness: "..round(global_max_fitness))
forms.settext(l_member, "Member: "..pop.member.."/"..population)
end
-------------------------------------------------------------------------------
-- gui.text(100, 0, "Distance: " .. distance, "white", "black")
-- gui.text(0, 0, course.name, "white", "topright")
-- gui.text(0,17, "X ".. string.format("%.3f", kart_x),"white","bottomleft")
-- gui.text(0,2, "Xv ".. string.format("%.3f", kart_xv),"white","bottomleft")
-- gui.text(120,17, "Y ".. string.format("%.3f", kart_y),"white","bottomleft")
-- gui.text(120,2, "Yv ".. string.format("%.3f", kart_yv),"white","bottomleft")
-- gui.text(240,17, "Z ".. string.format("%.3f", kart_z),"white","bottomleft")
-- gui.text(240,2, "Zv ".. string.format("%.3f", kart_zv),"white","bottomleft")
-- gui.text(360,17, "XYv " .. string.format("%.3f", XYspeed) .. " km/h","white","bottomleft")
-- gui.text(360,2, "XYZv " .. string.format("%.3f", round(XYZspeed)) .. " km/h","white","topleft")
-- gui.text(530,17, "sin " .. string.format("%.9f", k_sin),"white","bottomleft")
-- gui.text(530,2, "cos " .. string.format("%.9f", k_cos),"white","bottomleft")
end
function handle_form()
-- handle form options
if not forms.ischecked(hide_net) then
show_network()
end
if not forms.ischecked(hide_xyz_data) then
display_info()
end
end
function load_map()
the_course = {}
-- TODO find where the collision addresses end for each track
for addr = course.col_start, course.col_start + 0x9000, course.col_step do
local section = {}
section.p1 = {}
section.p2 = {}
section.p3 = {}
local the_attribute = mainmemory.read_s16_be(
addr + course.col_attr_offset
)
if the_attribute == course.tr_attr then
section.attribute = the_attribute
local p1_addr = mainmemory.read_s24_be(addr + course.p1_offset)
section.p1.x = mainmemory.read_s16_be(p1_addr)
section.p1.y = mainmemory.read_s16_be(p1_addr + 0x2)
section.p1.z = mainmemory.read_s16_be(p1_addr + 0x4)
local p2_addr = mainmemory.read_s24_be(addr + course.p2_offset)
section.p2.x = mainmemory.read_s16_be(p2_addr)
section.p2.y = mainmemory.read_s16_be(p2_addr + 0x2)
section.p2.z = mainmemory.read_s16_be(p2_addr + 0x4)
local p3_addr = mainmemory.read_s24_be(addr + course.p3_offset)
section.p3.x = mainmemory.read_s16_be(p3_addr)
section.p3.y = mainmemory.read_s16_be(p3_addr + 0x2)
section.p3.z = mainmemory.read_s16_be(p3_addr + 0x4)
the_course[#the_course + 1] = section
end
end
end
function initialize_population()
pop = new_pop()
for i = 1, pop.size do
local genome = new_genome()
mutate(genome)
speciate(genome)
end
refresh()
next_genome(false)
initialize_run(false)
create_backup("backup_"..state_file.."_gen_0.txt")
end
function new_pop()
local pop = {}
pop.size = population
pop.species = {}
pop.generation = 1
pop.current_species = 1
pop.current_genome = 0
pop.member = 0
pop.frame_count = -1
return pop
end
function new_species()
local species = {}
species.genomes = {}
species.fitness = 0
species.last_fitness = 0
species.improvement_age = 0
return species
end
function new_genome()
local genome = {}
-- gonna try to do this with just one genes table,
-- instead of nodes and connections
genome.genes = {}
-- keep track of how many nodes are in the network (not including outputs)
genome.num_neurons = num_inputs
genome.fitness = 0
genome.shared_fitness = 0
genome.network = {}
genome.received_trial = false
return genome
end
function new_gene(the_in, the_out, the_weight, the_enable, the_innovation)
local gene = {}
gene.in_node = the_in
gene.out_node = the_out
gene.weight = the_weight
gene.enable = the_enable
gene.innovation = the_innovation
return gene
end
function copy_all_species()
local species_copy = {}
for s = 1, #pop.species do
local species = new_species()
for g = 1, #pop.species[s].genomes do
table.insert(
species.genomes, copy_genome(pop.species[s].genomes[g])
)
end
table.insert(species_copy, species)
end
return species_copy
end
function copy_genome(genome)
g2 = new_genome()
for g = 1, #genome.genes do
table.insert(g2.genes, copy_gene(genome.genes[g]))
end
g2.num_neurons = genome.num_neurons
g2.fitness = genome.fitness
g2.shared_fitness = genome.shared_fitness
g2.received_trial = genome.received_trial
return g2
end
function copy_gene(gene)
local g2 = {}
g2.in_node = gene.in_node
g2.out_node = gene.out_node
g2.weight = gene.weight
g2.enable = gene.enable
g2.innovation = gene.innovation
return g2
end
function new_neuron(genome)
genome.num_neurons = genome.num_neurons + 1
return genome.num_neurons
end
function new_innovation(n1, n2)
-- TODO check for existing innovation
global_innovation = global_innovation + 1
-- pn(global_innovation)
return global_innovation
end
function mutate(genome)
-- can mutate each weight
if math.random() < mutate_weights_chance then
mutate_weights(genome)
end
-- structure mutations
-- can add connection
-- if math.random() <= mutate_structure_chance then
for i = 1, math.random(1, 2) do
add_connection(genome)
end
-- end
-- can add node
if math.random() < add_node_chance then
for i = 1, math.random(1,1) do
add_node(genome)
end
end
-- enable / disable
if math.random() < 0.5 then
mutate_enable(genome)
end
end
function mutate_weights(genome)
-- mutate the weights
for i = 1, #genome.genes do
local n = math.random(-1,1)
while n == 0 do
n = math.random(-1,1)
end
genome.genes[i].weight = (
genome.genes[i].weight + n * math.random() * weight_perturbation
)
end
end
function add_connection(genome)
-- add a new connection gene with a random weight
-- find two random neurons to connect, only one can be an input,
-- and they cannot be connected already
local n1
local n2
n1, n2 = two_random_neurons(genome)
-- generate a new gene with random weight, and in and out neurons
-- TODO check for existing innovation
local new_gene = new_gene(
n1, n2, -- in_node, out_node
math.random(), -- weight
true, -- enable bit
new_innovation(n1, n2)
)
for k, gene in pairs(genome.genes) do
if (gene.in_node == new_gene.in_node and
gene.out_node == new_gene.out_node) then
return -- TODO make this work better so it just tries again
end
end
table.insert(genome.genes, new_gene)
end
function add_node(genome)
if #genome.genes == 0 then
return
end
-- pick a connection to split
local old_connection = genome.genes[math.random(1, #genome.genes)]
old_connection.enable = false
local n1 = old_connection.in_node
local n2 = old_connection.out_node
local new_node_id = new_neuron(genome)
-- create two new connections
local new_connection_1 = new_gene(n1, new_node_id,
1.0,
true,
new_innovation(n1, new_node_id)
)
local new_connection_2 = new_gene(new_node_id, n2,
old_connection.weight,
true,
new_innovation(new_node_id, n2)
)
genome.num_neurons = genome.num_neurons + 1
table.insert(genome.genes, new_connection_1)
table.insert(genome.genes, new_connection_2)
end
function mutate_enable(genome)
for g = 1, #genome.genes do
if math.random() < 0.3 then
if genome.genes[g].enable then
genome.genes[g].enable = false
else
genome.genes[g].enable = true
end
end
end
end
function two_random_neurons(genome)
local n1
local n2
local neurons = {}
for i = 1, num_inputs do
neurons[i] = true
end
for o = 1, num_buttons do
neurons[max_nodes + o] = true
end
for i = 1, #genome.genes do
if genome.genes[i].in_node > num_inputs then
neurons[genome.genes[i].in_node] = true
end
if genome.genes[i].out_node > num_inputs then
neurons[genome.genes[i].out_node] = true
end
end
local num_neurons = 0
for _,_ in pairs(neurons) do
num_neurons = num_neurons + 1
end
-- choose if n2 will be output neuron or some other neuron
if num_neurons - 9 > num_inputs then
local excess_neurons = num_neurons - num_inputs - 9
local rando = math.random()
if rando < 0.33 then
n1 = math.random(1, 144)
n2 = math.random(145, 145 + excess_neurons)
elseif rando > 0.33 and rando < 0.66 then
n1 = math.random(145, 145 + excess_neurons)
n2 = math.random(1000001, 1000009)
else
n1 = math.random(1, num_neurons - 9)
n2 = math.random(1000001, 1000009)
end
else -- we don't have any other neurons but outputs
n1 = math.random(1, num_neurons - 9)
n2 = math.random(1000001, 1000009)
end
return n1, n2
end
function get_neurons(genome)
local neurons = {}
for i = 1, num_inputs do
neurons[i] = true
end
for o = 1, num_buttons do
neurons[max_nodes + o] = true
end
for i = 1, #genome.genes do
if genome.genes[i].in_node > num_inputs then
neurons[genome.genes[i].in_node] = true
end
if genome.genes[i].out_node > num_inputs then
neurons[genome.genes[i].out_node] = true
end
end
return neurons
end
function speciate(baby_genome)
local matched_a_species = false
local s = 0
for i = 1, #pop.species do
local genes1 = pop.species[i].genomes[1].genes
local genes2 = baby_genome.genes
if #genes2 < #genes1 then -- make sure the shorter genome is first
genes1, genes2 = genes2, genes1
end
cd = compatibility_distance(genes1, genes2)
if cd < compatibility_threshold then
table.insert(pop.species[i].genomes, baby_genome)
matched_a_species = true
s = i
break
end
end
if not matched_a_species then
local unique_species = new_species()
table.insert(unique_species.genomes, baby_genome)
table.insert(pop.species, unique_species)
end
return s
end
function compatibility_distance(genes1, genes2)
local E = excess_genes(genes1, genes2)
local D = disjoint_genes(genes1, genes2)
local N = math.max(#genes1, #genes2)
if N < 20 then N = 1 end
local W = sum_of_weight_differences(genes1, genes2) / (
#genes1 + #genes2 - E - D
)
return c1*E/N + c2*D/N + c3*W
end
function excess_genes(genes1, genes2)
local excess = 0
local highest_1 = 0
for i = 1, #genes1 do
if genes1[i].innovation > highest_1 then
highest_1 = genes1[i].innovation
end
end
local highest_2 = 0
for i = 1, #genes2 do
if genes2[i].innovation > highest_2 then
highest_2 = genes2[i].innovation
end
end
if highest_1 > highest_2 then
for i = 1, #genes1 do
if genes1[i].innovation > highest_2 then
excess = excess + 1
end
end
else
for i = 1, #genes2 do
if genes2[i].innovation > highest_1 then
excess = excess + 1
end
end
end
return excess
end
function disjoint_genes(genes1, genes2)
local disjoint = 0
for i = 1, #genes1 do
local found = false
for j = 1, #genes2 do
if genes1[i].innovation == genes2[j].innovation then
found = true
break
end
end
if not found then
disjoint = disjoint + 1
end
end
for i = 1, #genes2 do
local found = false
for j = 1, #genes1 do
if genes2[i].innovation == genes2[j].innovation then
found = true
break
end
end
if not found then
disjoint = disjoint + 1
end
end
return disjoint
end
function sum_of_weight_differences(genes1, genes2)
local sum_of_differences = 0
for i = 1, #genes1 do
for j = 1, #genes1 do
if genes1[i].innovation == genes2[j].innovation then
sum_of_differences = sum_of_differences + math.abs(
genes1[i].weight - genes2[j].weight
)
end
end
end
return sum_of_differences
end
function get_objects()
objects = {}
for addr = obj.addr, obj.stop, obj.step do
local object = {}
object.t = mainmemory.read_s16_be(addr) * 0.1
-- hmmm
if object.t > 1.1 and object.t < 1.3 then
object.t = 1.2
end
if object.t > 0.5 and object.t < 0.7 then
object.t = 0.6
end
if object.t > 0.6 and object.t < 0.8 then
object.t = 0.7
end
if object.t > 1.8 and object.t < 2 then
object.t = 1.9
end
-- make bad objects a negative value
if object.t == 2.6 or object.t == 1.3 or
object.t == 0.8 or object.t == 0.7 or
object.t == 0.6 or object.t == 3.1 or
object.t == 3.2 or object.t == 3 or
object.t == 1.9 then
object.t = -object.t
end
object.x = mainmemory.readfloat(addr + obj.x_offset, true)
object.y = mainmemory.readfloat(addr + obj.y_offset, true)
object.z = mainmemory.readfloat(addr + obj.z_offset, true)
if object.x == object.x and object.t ~= 0 and
object.t ~= 4.3 and in_box(object) then
objects[#objects + 1] = object
end
end
end
function get_box()
box = {}
box.tl = {}
box.tr = {}
box.bl = {}
box.br = {}
box.tl.x = 359 * k_cos + 180 * k_sin + kart_x
box.tl.z = 359 * k_sin - 180 * k_cos + kart_z
box.bl.x = -1 * k_cos + 180 * k_sin + kart_x
box.bl.z = -1 * k_sin - 180 * k_cos + kart_z
box.br.x = -1 * k_cos - 180 * k_sin + kart_x
box.br.z = -1 * k_sin + 180 * k_cos + kart_z
box.tr.x = 359 * k_cos - 180 * k_sin + kart_x
box.tr.z = 359 * k_sin + 180 * k_cos + kart_z
-- gui.text(
-- 220,130, string.format("%.3f", box.tl.x) .. ",Y," .. string.format(
-- "%.3f", box.tl.z
-- ),"white","topleft")
-- gui.text(
-- 480,130, string.format("%.3f", box.tr.x) .. ",Y," .. string.format(
-- "%.3f", box.tr.z),
-- "white","topleft")
-- gui.text(
-- 220,430, string.format("%.3f", box.bl.x) .. ",Y," .. string.format(
-- "%.3f", box.bl.z),
-- "white","topleft")
-- gui.text(
-- 480,430, string.format("%.3f", box.br.x) .. ",Y," .. string.format(
-- "%.3f", box.br.z),
-- "white","topleft")
end
function in_box(o)
-- top left to bottom left
local a = -(box.bl.z - box.tl.z)
local b = box.bl.x - box.tl.x
local c = -(a * box.tl.x + b * box.tl.z)
local b1 = s_sign(o, a, b, c) < 0
-- pn(b1)
-- bottom left to bottom right
a = -(box.br.z - box.bl.z)
b = box.br.x - box.bl.x
c = -(a * box.bl.x + b * box.bl.z)
local b2 = s_sign(o, a, b, c) < 0
-- bottom right to top right
a = -(box.tr.z - box.br.z)
b = box.tr.x - box.br.x
c = -(a * box.br.x + b * box.br.z)
local b3 = s_sign(o, a, b, c) < 0
-- top right to top left
a = -(box.tl.z - box.tr.z)
b = box.tl.x - box.tr.x
c = -(a * box.tr.x + b * box.tr.z)
local b4 = s_sign(o, a, b, c) < 0
return ((b1 == b2) and (b2 == b3) and (b3 == b4))
end
function s_sign(o, a, b, c)
return a * o.x + b * o.z + c
end
function get_tiles()
tiles = {}
for z = -165, 165, 30 do
for x = 344, 13, -30 do
local tile = {}
tile.n = #tiles + 1
tile.x = x * k_cos - z * k_sin + kart_x
tile.z = x * k_sin + z * k_cos + kart_z
tile.t = get_tile_attribute(tile.x, tile.z)
tiles[#tiles + 1] = tile
end
end
end
function get_tile_attribute(x, z)
-- could be an object, could be track, could be something else
-- objects
for i, o in ipairs(objects) do
local o_box = get_o_box(o)
if in_o_box(x, z, o_box) then
return o.t
end
end
-- track
for i, section in ipairs(the_course) do
if in_section(x, z, section) then
return section.attribute
end
end
-- something else
return -1
end
function get_o_box(o)
local o_box = {}
o_box.tl = {}
o_box.bl = {}
o_box.br = {}
o_box.tr = {}
o_box.tl.x = 15 * k_cos + 15 * k_sin + o.x
o_box.tl.z = 15 * k_sin - 15 * k_cos + o.z
o_box.bl.x = -15 * k_cos + 15 * k_sin + o.x
o_box.bl.z = -15 * k_sin - 15 * k_cos + o.z
o_box.br.x = -15 * k_cos - 15 * k_sin + o.x
o_box.br.z = -15 * k_sin + 15 * k_cos + o.z
o_box.tr.x = 15 * k_cos - 15 * k_sin + o.x
o_box.tr.z = 15 * k_sin + 15 * k_cos + o.z
o_box.y = o.y
return o_box
end
function in_o_box(x, z, o_box)
local o = {}
o.x = x
o.z = z
-- top left to bottom left
local a = -(o_box.bl.z - o_box.tl.z)
local b = o_box.bl.x - o_box.tl.x
local c = -(a * o_box.tl.x + b * o_box.tl.z)
local b1 = s_sign(o, a, b, c) < 0
-- bottom left to bottom right
a = -(o_box.br.z - o_box.bl.z)
b = o_box.br.x - o_box.bl.x
c = -(a * o_box.bl.x + b * o_box.bl.z)
local b2 = s_sign(o, a, b, c) < 0
-- bottom right to top right
a = -(o_box.tr.z - o_box.br.z)
b = o_box.tr.x - o_box.br.x
c = -(a * o_box.br.x + b * o_box.br.z)
local b3 = s_sign(o, a, b, c) < 0
-- top right to top left
a = -(o_box.tl.z - o_box.tr.z)
b = o_box.tl.x - o_box.tr.x
c = -(a * o_box.tr.x + b * o_box.tr.z)
local b4 = s_sign(o, a, b, c) < 0
local b5 = o_box.y > kart_y - 74 and o_box.y < kart_y + 74
return ((b1 == b2) and (b2 == b3) and (b3 == b4)) and b5
end
function in_section(x, z, s)
local b1 = t_sign(x, z, s.p1, s.p2) < 0
local b2 = t_sign(x, z, s.p2, s.p3) < 0
local b3 = t_sign(x, z, s.p3, s.p1) < 0
local b4 = s.p1.y > kart_y - 74 and s.p1.y < kart_y + 74
local b5 = s.p2.y > kart_y - 74 and s.p2.y < kart_y + 74
local b6 = s.p3.y > kart_y - 74 and s.p3.y < kart_y + 74
local b7 = ((b1 == b2) and (b2 == b3)) and b4 and b5 and b6
return b7
end
function t_sign(x, z, p2, p3)
return (x - p3.x) * (p2.z - p3.z) - (p2.x - p3.x) * (z - p3.z)
end
function get_inputs()
get_box()
get_objects()
get_tiles()
end
function get_outputs()
get_inputs()
local outputs = evaluate_network()
return outputs
end
function basic_ai()
-- this demonstrates how simple a solution can be
-- an interesting this about this is that it will play out the same every
-- single time. the game may seem random, but if the input to the game is
-- always the same, then the game will always play exactly the same.
-- the opponents will always drive in the same place, the same items will
-- received from item boxes, etc.
get_inputs()