MarI/O by SethBling

MarIO.lua

-- MarI/O by SethBling
-- Feel free to use this code, but please do not redistribute it.
-- Intended for use with the BizHawk emulator and Super Mario World or Super Mario Bros. ROM.
 
if gameinfo.getromname() == "Super Mario World (USA)" then
        Filename = "DP1.state"
        ButtonNames = {
                "A",
                "B",
                "X",
                "Y",
                "Up",
                "Down",
                "Left",
                "Right",
        }
elseif gameinfo.getromname() == "Super Mario Bros." then
        Filename = "SMB1-1.state"
        ButtonNames = {
                "A",
                "B",
                "Up",
                "Down",
                "Left",
                "Right",
        }
end
 
BoxRadius = 6
InputSize = (BoxRadius*2+1)*(BoxRadius*2+1)
 
Inputs = InputSize+1
Outputs = #ButtonNames
 
Population = 300
DeltaDisjoint = 2.0
DeltaWeights = 0.4
DeltaThreshold = 1.0
 
StaleSpecies = 15
 
MutateConnectionsChance = 0.25
PerturbChance = 0.90
CrossoverChance = 0.75
LinkMutationChance = 2.0
NodeMutationChance = 0.50
BiasMutationChance = 0.40
StepSize = 0.1
DisableMutationChance = 0.4
EnableMutationChance = 0.2
 
TimeoutConstant = 20
 
MaxNodes = 1000000
 
function getPositions()
        if gameinfo.getromname() == "Super Mario World (USA)" then
                marioX = memory.read_s16_le(0x94)
                marioY = memory.read_s16_le(0x96)
               
                local layer1x = memory.read_s16_le(0x1A);
                local layer1y = memory.read_s16_le(0x1C);
               
                screenX = marioX-layer1x
                screenY = marioY-layer1y
        elseif gameinfo.getromname() == "Super Mario Bros." then
                marioX = memory.readbyte(0x6D) * 0x100 + memory.readbyte(0x86)
                marioY = memory.readbyte(0x03B8)+16
       
                screenX = memory.readbyte(0x03AD)
                screenY = memory.readbyte(0x03B8)
        end
end
 
function getTile(dx, dy)
        if gameinfo.getromname() == "Super Mario World (USA)" then
                x = math.floor((marioX+dx+8)/16)
                y = math.floor((marioY+dy)/16)
               
                return memory.readbyte(0x1C800 + math.floor(x/0x10)*0x1B0 + y*0x10 + x%0x10)
        elseif gameinfo.getromname() == "Super Mario Bros." then
                local x = marioX + dx + 8
                local 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.readbyte(addr) ~= 0 then
                        return 1
                else
                        return 0
                end
        end
end
 
function getSprites()
        if gameinfo.getromname() == "Super Mario World (USA)" then
                local sprites = {}
                for slot=0,11 do
                        local status = memory.readbyte(0x14C8+slot)
                        if status ~= 0 then
                                spritex = memory.readbyte(0xE4+slot) + memory.readbyte(0x14E0+slot)*256
                                spritey = memory.readbyte(0xD8+slot) + memory.readbyte(0x14D4+slot)*256
                                sprites[#sprites+1] = {["x"]=spritex, ["y"]=spritey}
                        end
                end            
               
                return sprites
        elseif gameinfo.getromname() == "Super Mario Bros." then
                local sprites = {}
                for slot=0,4 do
                        local enemy = memory.readbyte(0xF+slot)
                        if enemy ~= 0 then
                                local ex = memory.readbyte(0x6E + slot)*0x100 + memory.readbyte(0x87+slot)
                                local ey = memory.readbyte(0xCF + slot)+24
                                sprites[#sprites+1] = {["x"]=ex,["y"]=ey}
                        end
                end
               
                return sprites
        end
end
 
function getExtendedSprites()
        if gameinfo.getromname() == "Super Mario World (USA)" then
                local extended = {}
                for slot=0,11 do
                        local number = memory.readbyte(0x170B+slot)
                        if number ~= 0 then
                                spritex = memory.readbyte(0x171F+slot) + memory.readbyte(0x1733+slot)*256
                                spritey = memory.readbyte(0x1715+slot) + memory.readbyte(0x1729+slot)*256
                                extended[#extended+1] = {["x"]=spritex, ["y"]=spritey}
                        end
                end            
               
                return extended
        elseif gameinfo.getromname() == "Super Mario Bros." then
                return {}
        end
end
 
function getInputs()
        getPositions()
       
        sprites = getSprites()
        extended = getExtendedSprites()
       
        local inputs = {}
       
        for dy=-BoxRadius*16,BoxRadius*16,16 do
                for dx=-BoxRadius*16,BoxRadius*16,16 do
                        inputs[#inputs+1] = 0
                       
                        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
 
function sigmoid(x)
        return 2/(1+math.exp(-4.9*x))-1
end
 
function newInnovation()
        pool.innovation = pool.innovation + 1
        return pool.innovation
end
 
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
 
function newSpecies()
        local species = {}
        species.topFitness = 0
        species.staleness = 0
        species.genomes = {}
        species.averageFitness = 0
       
        return species
end
 
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
 
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
 
function basicGenome()
        local genome = newGenome()
        local innovation = 1
 
        genome.maxneuron = Inputs
        mutate(genome)
       
        return genome
end
 
function newGene()
        local gene = {}
        gene.into = 0
        gene.out = 0
        gene.weight = 0.0
        gene.enabled = true
        gene.innovation = 0
       
        return gene
end
 
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
 
function newNeuron()
        local neuron = {}
        neuron.incoming = {}
        neuron.value = 0.0
       
        return neuron
end
 
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
 
function evaluateNetwork(network, inputs)
        table.insert(inputs, 1)
        if #inputs ~= Inputs then
                console.writeline("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 = "P1 " .. ButtonNames[o]
                if network.neurons[MaxNodes+o].value > 0 then
                        outputs[button] = true
                else
                        outputs[button] = false
                end
        end
       
        return outputs
end
 
function crossover(g1, g2)
        -- Make sure g1 is the higher fitness genome
        if g2.fitness > g1.fitness then
                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
 
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
 
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
 
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
 
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
 
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
 
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
 
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
 
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
 
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
       
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
 
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
 
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
 
function totalAverageFitness()
        local total = 0
        for s = 1,#pool.species do
                local species = pool.species[s]
                total = total + species.averageFitness
        end
 
        return total
end
 
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
 
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
 
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
 
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
 
 
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
 
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 .. "." .. forms.gettext(saveLoadFile))
end
       
function initializePool()
        pool = newPool()
 
        for i=1,Population do
                basic = basicGenome()
                addToSpecies(basic)
        end
 
        initializeRun()
end
 
function clearJoypad()
        controller = {}
        for b = 1,#ButtonNames do
                controller["P1 " .. ButtonNames[b]] = false
        end
        joypad.set(controller)
end
 
function initializeRun()
        savestate.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
 
function evaluateCurrent()
        local species = pool.species[pool.currentSpecies]
        local genome = species.genomes[pool.currentGenome]
 
        inputs = getInputs()
        controller = evaluateNetwork(genome.network, inputs)
       
        if controller["P1 Left"] and controller["P1 Right"] then
                controller["P1 Left"] = false
                controller["P1 Right"] = false
        end
        if controller["P1 Up"] and controller["P1 Down"] then
                controller["P1 Up"] = false
                controller["P1 Down"] = false
        end
 
        joypad.set(controller)
end
 
if pool == nil then
        initializePool()
end
 
 
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
 
function fitnessAlreadyMeasured()
        local species = pool.species[pool.currentSpecies]
        local genome = species.genomes[pool.currentGenome]
       
        return genome.fitness ~= 0
end
 
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.drawText(223, 24+8*o, ButtonNames[o], color, 9)
        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.drawBox(50-BoxRadius*5-3,70-BoxRadius*5-3,50+BoxRadius*5+2,70+BoxRadius*5+2,0xFF000000, 0x80808080)
        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.drawBox(cell.x-2,cell.y-2,cell.x+2,cell.y+2,opacity,color)
                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.drawLine(c1.x+1, c1.y, c2.x-3, c2.y, color)
                end
        end
       
        gui.drawBox(49,71,51,78,0x00000000,0x80FF0000)
       
        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
 
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
 
function savePool()
        local filename = forms.gettext(saveLoadFile)
        writeFile(filename)
end
 
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
 
function loadPool()
        local filename = forms.gettext(saveLoadFile)
        loadFile(filename)
end
 
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
 
function onExit()
        forms.destroy(form)
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)
 
 
while true do
        local backgroundColor = 0xD0FFFFFF
        if not forms.ischecked(hideBanner) then
                gui.drawBox(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 gameinfo.getromname() == "Super Mario World (USA)" and rightmost > 4816 then
                        fitness = fitness + 1000
                end
                if gameinfo.getromname() == "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 .. "." .. forms.gettext(saveLoadFile))
                end
               
                console.writeline("Gen " .. pool.generation .. " species " .. pool.currentSpecies .. " genome " .. pool.currentGenome .. " fitness: " .. fitness)
                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.drawText(0, 0, "Gen " .. pool.generation .. " species " .. pool.currentSpecies .. " genome " .. pool.currentGenome .. " (" .. math.floor(measured/total*100) .. "%)", 0xFF000000, 11)
                gui.drawText(0, 12, "Fitness: " .. math.floor(rightmost - (pool.currentFrame) / 2 - (timeout + timeoutBonus)*2/3), 0xFF000000, 11)
                gui.drawText(100, 12, "Max Fitness: " .. math.floor(pool.maxFitness), 0xFF000000, 11)
        end
               
        pool.currentFrame = pool.currentFrame + 1
 
        emu.frameadvance();
end