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NEATEvolve MAME
-- MarI/O by SethBling
-- Feel free to use this code, but please do not redistribute it.
-- usage: mame nes smb1 -window -autoboot_script NEATEvolve.lua
-- create savestate 1 at the start of the level you want it to learn
local Filename
local ButtonNames
local Game
local pool
local rightmost
local timeout
local marioX
local marioY
local screenX
local screenY
local controller
if emu.softname() == "smwu" then
Filename = "1"
ButtonNames = {
"A",
"B",
"X",
"Y",
"P1 Up",
"P1 Down",
"P1 Left",
"P1 Right",
}
Game = "Super Mario World (USA)"
elseif emu.softname() == "smb1" then
Filename = "1"
ButtonNames = {
"A",
"B",
"P1 Up",
"P1 Down",
"P1 Left",
"P1 Right",
}
Game = "Super Mario Bros."
end
local BoxRadius = 6
local InputSize = (BoxRadius*2+1)*(BoxRadius*2+1)
local Inputs = InputSize+1
local Outputs = #ButtonNames
local Population = 300
local DeltaDisjoint = 2.0
local DeltaWeights = 0.4
local DeltaThreshold = 1.0
local StaleSpecies = 15
local MutateConnectionsChance = 0.25
local PerturbChance = 0.90
local CrossoverChance = 0.75
local LinkMutationChance = 2.0
local NodeMutationChance = 0.50
local BiasMutationChance = 0.40
local StepSize = 0.1
local DisableMutationChance = 0.4
local EnableMutationChance = 0.2
local TimeoutConstant = 20
local MaxNodes = 1000000
local memory = manager:machine().devices[":maincpu"].spaces["program"]
local gui = select(2, next(manager:machine().screens))
local function writeFile(filename)
local file = io.open(filename, "w")
file:write(pool.generation .. "\n")
file:write(pool.maxFitness .. "\n")
file:write(#pool.species .. "\n")
for n,species in pairs(pool.species) do
file:write(species.topFitness .. "\n")
file:write(species.staleness .. "\n")
file:write(#species.genomes .. "\n")
for m,genome in pairs(species.genomes) do
file:write(genome.fitness .. "\n")
file:write(genome.maxneuron .. "\n")
for mutation,rate in pairs(genome.mutationRates) do
file:write(mutation .. "\n")
file:write(rate .. "\n")
end
file:write("done\n")
file:write(#genome.genes .. "\n")
for l,gene in pairs(genome.genes) do
file:write(gene.into .. " ")
file:write(gene.out .. " ")
file:write(gene.weight .. " ")
file:write(gene.innovation .. " ")
if(gene.enabled) then
file:write("1\n")
else
file:write("0\n")
end
end
end
end
file:close()
end
local function getPositions()
if Game == "Super Mario World (USA)" then
marioX = memory:read_i16(0x94)
marioY = memory:read_i16(0x96)
local layer1x = memory:read_i16(0x1A);
local layer1y = memory:read_i16(0x1C);
screenX = marioX-layer1x
screenY = marioY-layer1y
elseif Game == "Super Mario Bros." then
marioX = memory:read_u8(0x6D) * 0x100 + memory:read_u8(0x86)
marioY = memory:read_u8(0x03B8)+16
screenX = memory:read_u8(0x03AD)
screenY = memory:read_u8(0x03B8)
end
end
local function getTile(dx, dy)
local x, y
if Game == "Super Mario World (USA)" then
x = math.floor((marioX+dx+8)/16)
y = math.floor((marioY+dy)/16)
return memory:read_u8(0x7FC800 + math.floor(x/0x10)*0x1B0 + y*0x10 + x%0x10)
elseif Game == "Super Mario Bros." then
x = marioX + dx + 8
y = marioY + dy - 16
local page = math.floor(x/256)%2
local subx = math.floor((x%256)/16)
local suby = math.floor((y - 32)/16)
local addr = 0x500 + page*13*16+suby*16+subx
if suby >= 13 or suby < 0 then
return 0
end
if memory:read_u8(addr) ~= 0 then
return 1
else
return 0
end
end
end
local function getSprites()
if Game == "Super Mario World (USA)" then
local sprites = {}
for slot=0,11 do
local status = memory:read_u8(0x14C8+slot)
if status ~= 0 then
spritex = memory:read_u8(0xE4+slot) + memory:read_u8(0x14E0+slot)*256
spritey = memory:read_u8(0xD8+slot) + memory:read_u8(0x14D4+slot)*256
sprites[#sprites+1] = {["x"]=spritex, ["y"]=spritey}
end
end
return sprites
elseif Game == "Super Mario Bros." then
local sprites = {}
for slot=0,4 do
local enemy = memory:read_u8(0xF+slot)
if enemy ~= 0 then
local ex = memory:read_u8(0x6E + slot)*0x100 + memory:read_u8(0x87+slot)
local ey = memory:read_u8(0xCF + slot)+24
sprites[#sprites+1] = {["x"]=ex,["y"]=ey}
end
end
return sprites
end
end
local function getExtendedSprites()
if Game == "Super Mario World (USA)" then
local extended = {}
for slot=0,11 do
local number = memory:read_u8(0x170B+slot)
if number ~= 0 then
spritex = memory:read_u8(0x171F+slot) + memory:read_u8(0x1733+slot)*256
spritey = memory:read_u8(0x1715+slot) + memory:read_u8(0x1729+slot)*256
extended[#extended+1] = {["x"]=spritex, ["y"]=spritey}
end
end
return extended
elseif Game == "Super Mario Bros." then
return {}
end
end
local function getInputs()
getPositions()
local sprites = getSprites()
local extended = getExtendedSprites()
local inputs = {}
for dy=-BoxRadius*16,BoxRadius*16,16 do
for dx=-BoxRadius*16,BoxRadius*16,16 do
inputs[#inputs+1] = 0
local tile = getTile(dx, dy)
if tile == 1 and marioY+dy < 0x1B0 then
inputs[#inputs] = 1
end
for i = 1,#sprites do
distx = math.abs(sprites[i]["x"] - (marioX+dx))
disty = math.abs(sprites[i]["y"] - (marioY+dy))
if distx <= 8 and disty <= 8 then
inputs[#inputs] = -1
end
end
for i = 1,#extended do
distx = math.abs(extended[i]["x"] - (marioX+dx))
disty = math.abs(extended[i]["y"] - (marioY+dy))
if distx < 8 and disty < 8 then
inputs[#inputs] = -1
end
end
end
end
--mariovx = memory.read_s8(0x7B)
--mariovy = memory.read_s8(0x7D)
return inputs
end
local function sigmoid(x)
return 2/(1+math.exp(-4.9*x))-1
end
local function newInnovation()
pool.innovation = pool.innovation + 1
return pool.innovation
end
local function newPool()
local pool = {}
pool.species = {}
pool.generation = 0
pool.innovation = Outputs
pool.currentSpecies = 1
pool.currentGenome = 1
pool.currentFrame = 0
pool.maxFitness = 0
return pool
end
local function newSpecies()
local species = {}
species.topFitness = 0
species.staleness = 0
species.genomes = {}
species.averageFitness = 0
return species
end
local function newGenome()
local genome = {}
genome.genes = {}
genome.fitness = 0
genome.adjustedFitness = 0
genome.network = {}
genome.maxneuron = 0
genome.globalRank = 0
genome.mutationRates = {}
genome.mutationRates["connections"] = MutateConnectionsChance
genome.mutationRates["link"] = LinkMutationChance
genome.mutationRates["bias"] = BiasMutationChance
genome.mutationRates["node"] = NodeMutationChance
genome.mutationRates["enable"] = EnableMutationChance
genome.mutationRates["disable"] = DisableMutationChance
genome.mutationRates["step"] = StepSize
return genome
end
local function newGene()
local gene = {}
gene.into = 0
gene.out = 0
gene.weight = 0.0
gene.enabled = true
gene.innovation = 0
return gene
end
local function copyGene(gene)
local gene2 = newGene()
gene2.into = gene.into
gene2.out = gene.out
gene2.weight = gene.weight
gene2.enabled = gene.enabled
gene2.innovation = gene.innovation
return gene2
end
local function copyGenome(genome)
local genome2 = newGenome()
for g=1,#genome.genes do
table.insert(genome2.genes, copyGene(genome.genes[g]))
end
genome2.maxneuron = genome.maxneuron
genome2.mutationRates["connections"] = genome.mutationRates["connections"]
genome2.mutationRates["link"] = genome.mutationRates["link"]
genome2.mutationRates["bias"] = genome.mutationRates["bias"]
genome2.mutationRates["node"] = genome.mutationRates["node"]
genome2.mutationRates["enable"] = genome.mutationRates["enable"]
genome2.mutationRates["disable"] = genome.mutationRates["disable"]
return genome2
end
local function newNeuron()
local neuron = {}
neuron.incoming = {}
neuron.value = 0.0
return neuron
end
local function generateNetwork(genome)
local network = {}
network.neurons = {}
for i=1,Inputs do
network.neurons[i] = newNeuron()
end
for o=1,Outputs do
network.neurons[MaxNodes+o] = newNeuron()
end
table.sort(genome.genes, function (a,b)
return (a.out < b.out)
end)
for i=1,#genome.genes do
local gene = genome.genes[i]
if gene.enabled then
if network.neurons[gene.out] == nil then
network.neurons[gene.out] = newNeuron()
end
local neuron = network.neurons[gene.out]
table.insert(neuron.incoming, gene)
if network.neurons[gene.into] == nil then
network.neurons[gene.into] = newNeuron()
end
end
end
genome.network = network
end
local function evaluateNetwork(network, inputs)
table.insert(inputs, 1)
if #inputs ~= Inputs then
emu.print_error("Incorrect number of neural network inputs.")
return {}
end
for i=1,Inputs do
network.neurons[i].value = inputs[i]
end
for _,neuron in pairs(network.neurons) do
local sum = 0
for j = 1,#neuron.incoming do
local incoming = neuron.incoming[j]
local other = network.neurons[incoming.into]
sum = sum + incoming.weight * other.value
end
if #neuron.incoming > 0 then
neuron.value = sigmoid(sum)
end
end
local outputs = {}
for o=1,Outputs do
local button = ButtonNames[o]
if network.neurons[MaxNodes+o].value > 0 then
controller[button].state = 1
else
controller[button].state = 0
end
end
return outputs
end
local function crossover(g1, g2)
-- Make sure g1 is the higher fitness genome
if g2.fitness > g1.fitness then
local tempg = g1
g1 = g2
g2 = tempg
end
local child = newGenome()
local innovations2 = {}
for i=1,#g2.genes do
local gene = g2.genes[i]
innovations2[gene.innovation] = gene
end
for i=1,#g1.genes do
local gene1 = g1.genes[i]
local gene2 = innovations2[gene1.innovation]
if gene2 ~= nil and math.random(2) == 1 and gene2.enabled then
table.insert(child.genes, copyGene(gene2))
else
table.insert(child.genes, copyGene(gene1))
end
end
child.maxneuron = math.max(g1.maxneuron,g2.maxneuron)
for mutation,rate in pairs(g1.mutationRates) do
child.mutationRates[mutation] = rate
end
return child
end
local function randomNeuron(genes, nonInput)
local neurons = {}
if not nonInput then
for i=1,Inputs do
neurons[i] = true
end
end
for o=1,Outputs do
neurons[MaxNodes+o] = true
end
for i=1,#genes do
if (not nonInput) or genes[i].into > Inputs then
neurons[genes[i].into] = true
end
if (not nonInput) or genes[i].out > Inputs then
neurons[genes[i].out] = true
end
end
local count = 0
for _,_ in pairs(neurons) do
count = count + 1
end
local n = math.random(1, count)
for k,v in pairs(neurons) do
n = n-1
if n == 0 then
return k
end
end
return 0
end
local function containsLink(genes, link)
for i=1,#genes do
local gene = genes[i]
if gene.into == link.into and gene.out == link.out then
return true
end
end
end
local function pointMutate(genome)
local step = genome.mutationRates["step"]
for i=1,#genome.genes do
local gene = genome.genes[i]
if math.random() < PerturbChance then
gene.weight = gene.weight + math.random() * step*2 - step
else
gene.weight = math.random()*4-2
end
end
end
local function linkMutate(genome, forceBias)
local neuron1 = randomNeuron(genome.genes, false)
local neuron2 = randomNeuron(genome.genes, true)
local newLink = newGene()
if neuron1 <= Inputs and neuron2 <= Inputs then
--Both input nodes
return
end
if neuron2 <= Inputs then
-- Swap output and input
local temp = neuron1
neuron1 = neuron2
neuron2 = temp
end
newLink.into = neuron1
newLink.out = neuron2
if forceBias then
newLink.into = Inputs
end
if containsLink(genome.genes, newLink) then
return
end
newLink.innovation = newInnovation()
newLink.weight = math.random()*4-2
table.insert(genome.genes, newLink)
end
local function nodeMutate(genome)
if #genome.genes == 0 then
return
end
genome.maxneuron = genome.maxneuron + 1
local gene = genome.genes[math.random(1,#genome.genes)]
if not gene.enabled then
return
end
gene.enabled = false
local gene1 = copyGene(gene)
gene1.out = genome.maxneuron
gene1.weight = 1.0
gene1.innovation = newInnovation()
gene1.enabled = true
table.insert(genome.genes, gene1)
local gene2 = copyGene(gene)
gene2.into = genome.maxneuron
gene2.innovation = newInnovation()
gene2.enabled = true
table.insert(genome.genes, gene2)
end
local function enableDisableMutate(genome, enable)
local candidates = {}
for _,gene in pairs(genome.genes) do
if gene.enabled == not enable then
table.insert(candidates, gene)
end
end
if #candidates == 0 then
return
end
local gene = candidates[math.random(1,#candidates)]
gene.enabled = not gene.enabled
end
local function mutate(genome)
for mutation,rate in pairs(genome.mutationRates) do
if math.random(1,2) == 1 then
genome.mutationRates[mutation] = 0.95*rate
else
genome.mutationRates[mutation] = 1.05263*rate
end
end
if math.random() < genome.mutationRates["connections"] then
pointMutate(genome)
end
local p = genome.mutationRates["link"]
while p > 0 do
if math.random() < p then
linkMutate(genome, false)
end
p = p - 1
end
p = genome.mutationRates["bias"]
while p > 0 do
if math.random() < p then
linkMutate(genome, true)
end
p = p - 1
end
p = genome.mutationRates["node"]
while p > 0 do
if math.random() < p then
nodeMutate(genome)
end
p = p - 1
end
p = genome.mutationRates["enable"]
while p > 0 do
if math.random() < p then
enableDisableMutate(genome, true)
end
p = p - 1
end
p = genome.mutationRates["disable"]
while p > 0 do
if math.random() < p then
enableDisableMutate(genome, false)
end
p = p - 1
end
end
local function disjoint(genes1, genes2)
local i1 = {}
for i = 1,#genes1 do
local gene = genes1[i]
i1[gene.innovation] = true
end
local i2 = {}
for i = 1,#genes2 do
local gene = genes2[i]
i2[gene.innovation] = true
end
local disjointGenes = 0
for i = 1,#genes1 do
local gene = genes1[i]
if not i2[gene.innovation] then
disjointGenes = disjointGenes+1
end
end
for i = 1,#genes2 do
local gene = genes2[i]
if not i1[gene.innovation] then
disjointGenes = disjointGenes+1
end
end
local n = math.max(#genes1, #genes2)
return disjointGenes / n
end
local function weights(genes1, genes2)
local i2 = {}
for i = 1,#genes2 do
local gene = genes2[i]
i2[gene.innovation] = gene
end
local sum = 0
local coincident = 0
for i = 1,#genes1 do
local gene = genes1[i]
if i2[gene.innovation] ~= nil then
local gene2 = i2[gene.innovation]
sum = sum + math.abs(gene.weight - gene2.weight)
coincident = coincident + 1
end
end
return sum / coincident
end
local function sameSpecies(genome1, genome2)
local dd = DeltaDisjoint*disjoint(genome1.genes, genome2.genes)
local dw = DeltaWeights*weights(genome1.genes, genome2.genes)
return dd + dw < DeltaThreshold
end
local function rankGlobally()
local global = {}
for s = 1,#pool.species do
local species = pool.species[s]
for g = 1,#species.genomes do
table.insert(global, species.genomes[g])
end
end
table.sort(global, function (a,b)
return (a.fitness < b.fitness)
end)
for g=1,#global do
global[g].globalRank = g
end
end
local function calculateAverageFitness(species)
local total = 0
for g=1,#species.genomes do
local genome = species.genomes[g]
total = total + genome.globalRank
end
species.averageFitness = total / #species.genomes
end
local function totalAverageFitness()
local total = 0
for s = 1,#pool.species do
local species = pool.species[s]
total = total + species.averageFitness
end
return total
end
local function cullSpecies(cutToOne)
for s = 1,#pool.species do
local species = pool.species[s]
table.sort(species.genomes, function (a,b)
return (a.fitness > b.fitness)
end)
local remaining = math.ceil(#species.genomes/2)
if cutToOne then
remaining = 1
end
while #species.genomes > remaining do
table.remove(species.genomes)
end
end
end
local function breedChild(species)
local child = {}
if math.random() < CrossoverChance then
g1 = species.genomes[math.random(1, #species.genomes)]
g2 = species.genomes[math.random(1, #species.genomes)]
child = crossover(g1, g2)
else
g = species.genomes[math.random(1, #species.genomes)]
child = copyGenome(g)
end
mutate(child)
return child
end
local function removeStaleSpecies()
local survived = {}
for s = 1,#pool.species do
local species = pool.species[s]
table.sort(species.genomes, function (a,b)
return (a.fitness > b.fitness)
end)
if species.genomes[1].fitness > species.topFitness then
species.topFitness = species.genomes[1].fitness
species.staleness = 0
else
species.staleness = species.staleness + 1
end
if species.staleness < StaleSpecies or species.topFitness >= pool.maxFitness then
table.insert(survived, species)
end
end
pool.species = survived
end
local function removeWeakSpecies()
local survived = {}
local sum = totalAverageFitness()
for s = 1,#pool.species do
local species = pool.species[s]
breed = math.floor(species.averageFitness / sum * Population)
if breed >= 1 then
table.insert(survived, species)
end
end
pool.species = survived
end
local function addToSpecies(child)
local foundSpecies = false
for s=1,#pool.species do
local species = pool.species[s]
if not foundSpecies and sameSpecies(child, species.genomes[1]) then
table.insert(species.genomes, child)
foundSpecies = true
end
end
if not foundSpecies then
local childSpecies = newSpecies()
table.insert(childSpecies.genomes, child)
table.insert(pool.species, childSpecies)
end
end
local function newGeneration()
cullSpecies(false) -- Cull the bottom half of each species
rankGlobally()
removeStaleSpecies()
rankGlobally()
for s = 1,#pool.species do
local species = pool.species[s]
calculateAverageFitness(species)
end
removeWeakSpecies()
local sum = totalAverageFitness()
local children = {}
for s = 1,#pool.species do
local species = pool.species[s]
breed = math.floor(species.averageFitness / sum * Population) - 1
for i=1,breed do
table.insert(children, breedChild(species))
end
end
cullSpecies(true) -- Cull all but the top member of each species
while #children + #pool.species < Population do
local species = pool.species[math.random(1, #pool.species)]
table.insert(children, breedChild(species))
end
for c=1,#children do
local child = children[c]
addToSpecies(child)
end
pool.generation = pool.generation + 1
writeFile("backup." .. pool.generation .. "." .. emu.softname() .. emu.romname() .. ".pool")
end
local function basicGenome()
local genome = newGenome()
local innovation = 1
genome.maxneuron = Inputs
mutate(genome)
return genome
end
local function joypad_set(buttons)
for name, button in pairs(buttons) do
button.field:set_value(button.state)
end
end
local function clearJoypad()
controller = {}
for b = 1,#ButtonNames do
for name, port in pairs(manager:machine():ioport().ports) do
if name:match("ctrl1") then
for fname, field in pairs(port.fields) do
if fname == ButtonNames[b] then
local button = {}
button.port = port
button.field = field
button.state = 0
controller[ButtonNames[b]] = button
end
end
break
end
end
end
joypad_set(controller)
end
local function evaluateCurrent()
local species = pool.species[pool.currentSpecies]
local genome = species.genomes[pool.currentGenome]
inputs = getInputs()
evaluateNetwork(genome.network, inputs)
if controller["P1 Left"].state ~= 0 and controller["P1 Right"].state ~= 0 then
controller["P1 Left"].state = 0
controller["P1 Right"].state = 0
end
if controller["P1 Up"].state ~= 0 and controller["P1 Down"].state ~= 0 then
controller["P1 Up"].state = 0
controller["P1 Down"].state = 0
end
joypad_set(controller)
end
local function initializeRun()
manager:machine():load(Filename);
rightmost = 0
pool.currentFrame = 0
timeout = TimeoutConstant
clearJoypad()
local species = pool.species[pool.currentSpecies]
local genome = species.genomes[pool.currentGenome]
generateNetwork(genome)
evaluateCurrent()
end
local function initializePool()
pool = newPool()
for i=1,Population do
basic = basicGenome()
addToSpecies(basic)
end
initializeRun()
end
if pool == nil then
initializePool()
end
local function nextGenome()
pool.currentGenome = pool.currentGenome + 1
if pool.currentGenome > #pool.species[pool.currentSpecies].genomes then
pool.currentGenome = 1
pool.currentSpecies = pool.currentSpecies+1
if pool.currentSpecies > #pool.species then
newGeneration()
pool.currentSpecies = 1
end
end
end
local function fitnessAlreadyMeasured()
local species = pool.species[pool.currentSpecies]
local genome = species.genomes[pool.currentGenome]
return genome.fitness ~= 0
end
local function displayGenome(genome)
local network = genome.network
local cells = {}
local i = 1
local cell = {}
for dy=-BoxRadius,BoxRadius do
for dx=-BoxRadius,BoxRadius do
cell = {}
cell.x = 50+5*dx
cell.y = 70+5*dy
cell.value = network.neurons[i].value
cells[i] = cell
i = i + 1
end
end
local biasCell = {}
biasCell.x = 80
biasCell.y = 110
biasCell.value = network.neurons[Inputs].value
cells[Inputs] = biasCell
for o = 1,Outputs do
cell = {}
cell.x = 220
cell.y = 30 + 8 * o
cell.value = network.neurons[MaxNodes + o].value
cells[MaxNodes+o] = cell
local color
if cell.value > 0 then
color = 0xFF0000FF
else
color = 0xFF000000
end
gui:draw_text(223, 24+8*o, ButtonNames[o], color)
end
for n,neuron in pairs(network.neurons) do
cell = {}
if n > Inputs and n <= MaxNodes then
cell.x = 140
cell.y = 40
cell.value = neuron.value
cells[n] = cell
end
end
for n=1,4 do
for _,gene in pairs(genome.genes) do
if gene.enabled then
local c1 = cells[gene.into]
local c2 = cells[gene.out]
if gene.into > Inputs and gene.into <= MaxNodes then
c1.x = 0.75*c1.x + 0.25*c2.x
if c1.x >= c2.x then
c1.x = c1.x - 40
end
if c1.x < 90 then
c1.x = 90
end
if c1.x > 220 then
c1.x = 220
end
c1.y = 0.75*c1.y + 0.25*c2.y
end
if gene.out > Inputs and gene.out <= MaxNodes then
c2.x = 0.25*c1.x + 0.75*c2.x
if c1.x >= c2.x then
c2.x = c2.x + 40
end
if c2.x < 90 then
c2.x = 90
end
if c2.x > 220 then
c2.x = 220
end
c2.y = 0.25*c1.y + 0.75*c2.y
end
end
end
end
gui:draw_box(50-BoxRadius*5-3,70-BoxRadius*5-3,50+BoxRadius*5+2,70+BoxRadius*5+2, 0x80808080,0xFF000000)
for n,cell in pairs(cells) do
if n > Inputs or cell.value ~= 0 then
local color = math.floor((cell.value+1)/2*256)
if color > 255 then color = 255 end
if color < 0 then color = 0 end
local opacity = 0xFF000000
if cell.value == 0 then
opacity = 0x50000000
end
color = opacity + color*0x10000 + color*0x100 + color
gui:draw_box(cell.x-2,cell.y-2,cell.x+2,cell.y+2,color,opacity)
end
end
for _,gene in pairs(genome.genes) do
if gene.enabled then
local c1 = cells[gene.into]
local c2 = cells[gene.out]
local opacity = 0xA0000000
if c1.value == 0 then
opacity = 0x20000000
end
local color = 0x80-math.floor(math.abs(sigmoid(gene.weight))*0x80)
if gene.weight > 0 then
color = opacity + 0x8000 + 0x10000*color
else
color = opacity + 0x800000 + 0x100*color
end
gui:draw_line(c1.x+1, c1.y, c2.x-3, c2.y, color)
end
end
gui:draw_box(49,71,51,78,0x80FF0000,0x00000000)
--[[ if forms.ischecked(showMutationRates) then
local pos = 100
for mutation,rate in pairs(genome.mutationRates) do
gui.drawText(100, pos, mutation .. ": " .. rate, 0xFF000000, 10)
pos = pos + 8
end
end]]
end
local function savePool()
local filename = emu.softname() .. emu.romname() .. ".pool"
writeFile(filename)
end
local function loadFile(filename)
local file = io.open(filename, "r")
pool = newPool()
pool.generation = file:read("*number")
pool.maxFitness = file:read("*number")
-- forms.settext(maxFitnessLabel, "Max Fitness: " .. math.floor(pool.maxFitness))
local numSpecies = file:read("*number")
for s=1,numSpecies do
local species = newSpecies()
table.insert(pool.species, species)
species.topFitness = file:read("*number")
species.staleness = file:read("*number")
local numGenomes = file:read("*number")
for g=1,numGenomes do
local genome = newGenome()
table.insert(species.genomes, genome)
genome.fitness = file:read("*number")
genome.maxneuron = file:read("*number")
local line = file:read("*line")
while line ~= "done" do
genome.mutationRates[line] = file:read("*number")
line = file:read("*line")
end
local numGenes = file:read("*number")
for n=1,numGenes do
local gene = newGene()
table.insert(genome.genes, gene)
local enabled
gene.into, gene.out, gene.weight, gene.innovation, enabled = file:read("*number", "*number", "*number", "*number", "*number")
if enabled == 0 then
gene.enabled = false
else
gene.enabled = true
end
end
end
end
file:close()
while fitnessAlreadyMeasured() do
nextGenome()
end
initializeRun()
pool.currentFrame = pool.currentFrame + 1
end
local function loadPool()
local filename = emu.softname() .. emu.romname() .. ".pool"
loadFile(filename)
end
local function playTop()
local maxfitness = 0
local maxs, maxg
for s,species in pairs(pool.species) do
for g,genome in pairs(species.genomes) do
if genome.fitness > maxfitness then
maxfitness = genome.fitness
maxs = s
maxg = g
end
end
end
pool.currentSpecies = maxs
pool.currentGenome = maxg
pool.maxFitness = maxfitness
-- forms.settext(maxFitnessLabel, "Max Fitness: " .. math.floor(pool.maxFitness))
initializeRun()
pool.currentFrame = pool.currentFrame + 1
return
end
writeFile("temp.pool")
--event.onexit(onExit)
--[[form = forms.newform(200, 260, "Fitness")
maxFitnessLabel = forms.label(form, "Max Fitness: " .. math.floor(pool.maxFitness), 5, 8)
showNetwork = forms.checkbox(form, "Show Map", 5, 30)
showMutationRates = forms.checkbox(form, "Show M-Rates", 5, 52)
restartButton = forms.button(form, "Restart", initializePool, 5, 77)
saveButton = forms.button(form, "Save", savePool, 5, 102)
loadButton = forms.button(form, "Load", loadPool, 80, 102)
saveLoadFile = forms.textbox(form, Filename .. ".pool", 170, 25, nil, 5, 148)
saveLoadLabel = forms.label(form, "Save/Load:", 5, 129)
playTopButton = forms.button(form, "Play Top", playTop, 5, 170)
hideBanner = forms.checkbox(form, "Hide Banner", 5, 190)]]
emu.register_frame_done(function()
local backgroundColor = 0xD0FFFFFF
-- if not forms.ischecked(hideBanner) then
gui:draw_box(0, 0, 300, 26, backgroundColor, backgroundColor)
-- end
local species = pool.species[pool.currentSpecies]
local genome = species.genomes[pool.currentGenome]
-- if forms.ischecked(showNetwork) then
displayGenome(genome)
-- end
if pool.currentFrame%5 == 0 then
evaluateCurrent()
end
joypad_set(controller)
getPositions()
if marioX > rightmost then
rightmost = marioX
timeout = TimeoutConstant
end
timeout = timeout - 1
local timeoutBonus = pool.currentFrame / 4
if timeout + timeoutBonus <= 0 then
local fitness = rightmost - pool.currentFrame / 2
if Game == "Super Mario World (USA)" and rightmost > 4816 then
fitness = fitness + 1000
end
if Game == "Super Mario Bros." and rightmost > 3186 then
fitness = fitness + 1000
end
if fitness == 0 then
fitness = -1
end
genome.fitness = fitness
if fitness > pool.maxFitness then
pool.maxFitness = fitness
--forms.settext(maxFitnessLabel, "Max Fitness: " .. math.floor(pool.maxFitness))
writeFile("backup." .. pool.generation .. "." .. emu.softname() .. emu.romname() .. ".pool")
end
emu.print_error("Gen " .. pool.generation .. " species " .. pool.currentSpecies .. " genome " .. pool.currentGenome .. " fitness: " .. fitness .. " marioX = " .. marioX .. " marioY = " .. marioY)
pool.currentSpecies = 1
pool.currentGenome = 1
while fitnessAlreadyMeasured() do
nextGenome()
end
initializeRun()
end
local measured = 0
local total = 0
for _,species in pairs(pool.species) do
for _,genome in pairs(species.genomes) do
total = total + 1
if genome.fitness ~= 0 then
measured = measured + 1
end
end
end
-- if not forms.ischecked(hideBanner) then
gui:draw_text(0, 0, "Gen " .. pool.generation .. " species " .. pool.currentSpecies .. " genome " .. pool.currentGenome .. " (" .. math.floor(measured/total*100) .. "%)", 0xFF000000)
gui:draw_text(0, 12, "Fitness: " .. math.floor(rightmost - (pool.currentFrame) / 2 - (timeout + timeoutBonus)*2/3), 0xFF000000)
gui:draw_text(100, 12, "Max Fitness: " .. math.floor(pool.maxFitness), 0xFF000000)
-- end
pool.currentFrame = pool.currentFrame + 1
end)
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