Recipe: 3neuro16tryhardProSmallStepNotePub.Lua

created by zo3xiaJonWeinberg

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• Name: 3neuro16tryhardProSmallStepNotePub.Lua
• ID: 104461
• Shared with: Public
• Parent: 3neuro16tryhardProSmallStepNote.Lua
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  • 3neuro16tryhardProSmallStepNotePubCut.Lua
• Created on: February 09, 2021 at 12:37 PM UTC
• Updated on: February 09, 2021 at 12:37 PM UTC
• Description:

  Login to Fold.it to download ; click Show Output terminal button. ; open Behavior tab see fitness rising ; keep info width within 1 line ; for hover info. ; This neural network A.i. is a work ; in progress. ; Welcome to rate or expand the ; hidden layers or add inputs, ; outputs like parameters ; or teach it to count. ; An earlier ReLU version already ; did somewhat OK ; on the XOR problem, though it just ; converged its output from 80 to 0 ; for both true 1 and false 0.. ; Maybe try ReLU for hiddens only.

  Feb. 9, more comments, ; and save shifu NN as note ; which can be copied by user. ; publishing. ; quick fix of bug where pokemon 1 ; could not be recorded as strongest ; or 2nd strongest. ; Feb. 7. noticed a.i. using time ; consuming action MSG All ; perhaps to bide time ; because I did deduct negative ; score somewhat (alpha=0.1) ; but divided it by time. ; Update feb. 2021, fixed index out ; of bounds for insert.

  Jan. 2021 ; Fixed Design bug del. res ; out of bounds (del. 2x). ; Still has out of bounds insert bug. ; Discarding update ideal14's ; advanced evolution in favor of ; "disciple exceeds master". ; Also trying out muta worst seg.

  2020 ; It likes Rebuild worst for prediction. ; Fixed choosing best scorer ; subtle bug. ; Had been assigning non-weakest ; as strongest, so last critter tended ; to be "strongest". ; Also added runner-up. ; now without creditbest. ; and, or? ; greyscale and teacher ; w/o random, outputs converge to 1 ; after waking from a 9 hour sleep ; Now with random inputs. ; W/ random inputs, ; convergence after 1 hour (hora) ; realized the xor function was bugged ; fixed xor, changed stuff ; converges to 98.5% fitness ; after 10 min. ; "Code 871". ; now IRL problem, clash. ; middle ground 0.9 after 5 mins

Code

--keep blank line at top 4 debug

HASMUTABLE=false
descrTxt=puzzle.GetDescription()
if #descrTxt>0 and (descrTxt:find("design") or descrTxt:find("designs")) then        
HASMUTABLE=true        IDEALCHECK=true        HANDFOLD=true    end
--copied from AFK3.1.1 using new foldit editor

--if HASMUTABLE then environInput1=1 else environInput1=0 end
print("muta ")
print(HASMUTABLE) --can't cat 

-----
--So I cut and pasted these functions from BWP here for AFK.
NonLockedSegList={}
function segCnt() return structure.GetCount() end --jon
function IsUnlockedSeg( seg1 )
   return not structure.IsLocked( seg1 )
end
function FindAllMovableSegs( )
    --segCnt=structure.GetCount() --jon lazy
    NonLockedSegList={} --jon reinit in case deleting res.
    for i=1, structure.GetCount() do --jon
        if structure.IsLocked( i ) then 
            PuzzleHasLockedSegs = true
        else
            NonLockedSegList[ #NonLockedSegList + 1] = i
        end
    end
    if PuzzleHasLockedSegs then
        for i=1, structure.GetCount() do --jon
            if IsUnlockedSeg( i ) then 
                MinUnlockedSeg = i
                break
            end
        end
        for i=segCnt(), 1, -1 do
            if IsUnlockedSeg( i ) then 
                MaxUnlockedSeg = i
                break
            end
        end
    end
    return false
end
FindAllMovableSegs()
------

------------A.i. learns v7 filters
performAction={}
actionDescription={}
function printTimeAndScore(startTime, scoreGain, currentStateString)
    local ss = (os.time() - startTime) % 60
    local mm = (((os.time() - startTime - ss) % 3600) / 60)
    local hh = (os.time() - startTime - mm*60 - ss) / 3600
    print("Time: " .. string.format("%02d", hh) .. ":" .. string.format("%02d", mm) .. ":" .. 
string.format("%02d", ss) .. ". " .. currentStateString)
    print(" Score: " .. current.GetEnergyScore() .. 
", Total: +" .. scoreGain)
end
function initializeActions()
    performAction = {}
    actionDescription = {}

    performAction[0] = function()
        local ss=math.random(1,structure.GetCount()-3)
        selection.SelectRange(ss,ss+3)
        structure.MutateSidechainsSelected(1) --All(1)
    end
    actionDescription[0] = "Mutate(1)"

    performAction[1] = function()
        structure.WiggleAll(1)
    end
    actionDescription[1] = "Wiggle("

    performAction[2] = function()
        local startSegmentNumber = math.random(1, structure.GetCount() - 9)
        local endSegmentNumber = math.random(startSegmentNumber + 8, structure.GetCount())
        band.AddBetweenSegments(startSegmentNumber, endSegmentNumber)
        band.SetStrength(1, 10)
        band.SetGoalLength(1, structure.GetDistance(startSegmentNumber, endSegmentNumber) * 0.9)
    end
    actionDescription[2] = "Add random band"
    performAction[3] = function()
        band.DeleteAll()
    end
    actionDescription[3] = "Delete all bands"

    recentbest.Save() --overwrite it first
    performAction[4] = function()
        recentbest.Restore() --still somehow accessing
        FindAllMovableSegs()
        --print("banned")
    end
    actionDescription[4] = "Restore recent best"

    performAction[5] = function()
        local startSegmentNumber = math.random(1,structure.GetCount() - 3)
        selection.DeselectAll()
        selection.SelectRange(startSegmentNumber, startSegmentNumber + 3)
        structure.RebuildSelected(2)
        selection.DeselectAll()
    end
    actionDescription[5] = "Rebuild random segment"
    performAction[6] = function()
        behavior.SetClashImportance(1)
    end
    actionDescription[6] = "Set clash importance to 1"
    performAction[7] = function()
        behavior.SetClashImportance(0.5)
    end
    actionDescription[7] = "Set clash importance to 0.5"
    performAction[8] = function()
        behavior.SetClashImportance(0.02)
    end
    actionDescription[8] = "Set clash importance to 0.02"
    performAction[9] = function()
        local startSegmentNumber = math.random(1, structure.GetCount() - 3)
        selection.DeselectAll()
        selection.SelectRange(startSegmentNumber, startSegmentNumber + 3)
        structure.IdealizeSelected()
        selection.DeselectAll()
    end
    actionDescription[9] = "Idealize random segment"
    performAction[10] = function()
        local lengthOfSegment = math.random(1, 3)
        local segmentInformation = {}
        local workSegmentNumber = math.random(1, 3)
        local function sortSegments(segmentInformation)
            for i = 1, #segmentInformation - 1 do
                for j = i + 1, #segmentInformation do
                    if segmentInformation[i][3] > segmentInformation[j][3] then
                        segmentInformation[i], segmentInformation[j] = segmentInformation[j], 
segmentInformation[i]
                    end
                end
            end
            return segmentInformation
        end
        for i = 1, structure.GetCount() - lengthOfSegment + 1 do
            segmentInformation[i] = {i, i + lengthOfSegment - 1, current.GetSegmentEnergyScore(i) }
            for j = 2, lengthOfSegment do
                segmentInformation[i][3] = segmentInformation[i][3] + current.GetSegmentEnergyScore(i 
+ j - 1)
            end
        end
        segmentInformation = sortSegments(segmentInformation)
        selection.DeselectAll()
        selection.SelectRange(math.max(segmentInformation[workSegmentNumber][1] - 1, 1), 
math.min(segmentInformation[workSegmentNumber][2] + 1, structure.GetCount()))
        structure.RebuildSelected(2)
        selection.DeselectAll()
    end
    actionDescription[10] = "Rebuild worst segment"

    performAction[11]=function()
        behavior.SetFiltersDisabled(true)
    end
    actionDescription[11]="disable filters"
    performAction[12]=function()
        behavior.SetFiltersDisabled(false)
    end
    actionDescription[12]="enable filters"

    table.insert(performAction,function()
        FindAllMovableSegs()
        cut=NonLockedSegList[math.random(#NonLockedSegList)] --plz only unlocked
        structure.InsertCut(cut)
        behavior.UseCutBands(false)
        seg=NonLockedSegList[math.random(#NonLockedSegList)] --plz not the cut
        options={"h","l","e"}
        ss=options[math.random(3)]
        structure.SetSecondaryStructure(seg,ss)
        selection.DeselectAll()
        selection.Select(seg)
        structure.IdealSSSelected() --need cut beforehand in linker
        behavior.UseCutBands(true)
        behavior.SetClashImportance(1)
        structure.WiggleAll(1)
        structure.DeleteCut(cut)
    end)
    table.insert(actionDescription,"random SS, idealSS")

    table.insert(performAction,function() structure.LocalWiggleAll(1) end)
    table.insert(actionDescription,"LwA")

    table.insert(performAction,function() 
        FindAllMovableSegs()
        structure.InsertResidue(NonLockedSegList[math.random(#NonLockedSegList) ])
        FindAllMovableSegs()
        --structure.WiggleAll(1) --debug
    end)
    table.insert(actionDescription,"ins")

    table.insert(performAction,function()
        FindAllMovableSegs() 
        structure.DeleteResidue(NonLockedSegList[math.random(#NonLockedSegList) ])
        FindAllMovableSegs()
        --structure.WiggleAll(1) --debug
    end)
    table.insert(actionDescription,"del. seg, may cause band glitch")

    table.insert(performAction,function() puzzle.StartOver() FindAllMovableSegs() end)
    table.insert(actionDescription,"reset") --multi

    table.insert(performAction,function() save.Quicksave(3) end)
    table.insert(actionDescription,"save3")

    table.insert(performAction,function() save.Quickload(3) FindAllMovableSegs() end)
    table.insert(actionDescription,"load3")

    table.insert(performAction,function() creditbest.Restore() FindAllMovableSegs() end)
    table.insert(actionDescription,"credit")

    table.insert(performAction,function() absolutebest.Restore() FindAllMovableSegs() end)
    table.insert(actionDescription,"abs best")


    table.insert(performAction,function()
        cuts=structure.GetCuts()
        for i=1,#cuts do
            structure.DeleteCut(cuts[i])
        end
    end)
    table.insert(actionDescription,"del. cuts")

    table.insert(performAction,function()
        local ss=math.random(1,structure.GetCount()-3)
        selection.SelectRange(ss,ss+3)
        structure.ShakeSidechainsSelected(1) --All(1)
    end)
    table.insert(actionDescription,"shake(1)")

    table.insert(performAction,function()
        local lengthOfSegment = math.random(1, 3)
        local segmentInformation = {}
        local workSegmentNumber = math.random(1, 3) --jon asks if Quicksort
        local function sortSegments(segmentInformation)
            for i = 1, #segmentInformation - 1 do
                for j = i + 1, #segmentInformation do
                    if segmentInformation[i][3] > segmentInformation[j][3] then
                        segmentInformation[i], segmentInformation[j] = segmentInformation[j], 
segmentInformation[i]
                    end
                end
            end
            return segmentInformation
        end
        for i = 1, structure.GetCount() - lengthOfSegment + 1 do
            segmentInformation[i] = {i, i + lengthOfSegment - 1, current.GetSegmentEnergyScore(i) }
            for j = 2, lengthOfSegment do
                segmentInformation[i][3] = segmentInformation[i][3] + current.GetSegmentEnergyScore(i 
+ j - 1)
            end
        end
        segmentInformation = sortSegments(segmentInformation)
        selection.DeselectAll()
        selection.SelectRange(math.max(
            segmentInformation[workSegmentNumber][1] - 1, 1), 
            math.min(segmentInformation[workSegmentNumber][2] + 1, structure.GetCount()))
        structure.MutateSidechainsSelected(2)
        selection.DeselectAll()
    end)
    table.insert(actionDescription,"muta worst segment")
    
    table.insert(performAction, function() 
        i=math.random(1,structure.GetCount()) -- do --abridged for debugging 
        structure.SetAminoAcid(i,"e")
    --e for msg 
        --acids arndceqghilkmfpstwyv
    --g for glycine
    --v for valine, suggested by Enzyme for 1947
        --end
    end)
    table.insert(actionDescription,"set amino msg")

    table.insert(performAction, function() 
        i=math.random(structure.GetCount())
        aminos="arndceqghilkmfpstwyv"
        choice=math.random(#aminos)
        local char = aminos:sub(choice,choice)
structure.SetAminoAcid(i,char)
    --e for msg 
    
    --g for glycine
    --v for valine, suggested by Enzyme for 1947
       
    end)
    table.insert(actionDescription,"set amino rand")


    --imported from AiLearns22
    performAction[13]=function()
        --Bands in Space
        local s1=math.random(structure.GetCount())
        local str=math.random(0.1,1)
            local len=math.random(20)
            local theta = math.acos(math.random()) --jon: arccosine
            local phi = 2 * math.pi * math.random()
            local segmentXAxis=0
            local segmentYAxis=0
            while true do --all 3 must be different
                segmentXAxis = math.random(structure.GetCount())--segCnt) --jon
                segmentYAxis = math.random(structure.GetCount())--segCnt) --jon
                if segmentXAxis~=s1 and segmentYAxis~=s1 and segmentXAxis~=segmentYAxis then break end
            end
            --{segmentOrigin, segmentXAxis, segmentYAxis, rho, theta, phi}
            band.Add(s1, segmentXAxis, segmentYAxis, len, theta, phi, str)
           --bands.AddBand(b)
         --puzzle.StartOver()
        
    end
    actionDescription[13]="band in space"

    table.insert(performAction, function() structure.WiggleAll(1) end)
    table.insert(actionDescription, "Wiggle all, moved from action 0 because Lua starts at 1")

    table.insert(performAction, function() structure.LocalWiggleAll(1) end )
    table.insert(actionDescription, "local wiggle all inspired by BWP")

    table.insert(performAction, function()
        local seg=math.random(structure.GetCount())
        selection.SelectRange(seg,math.max(seg,math.random(structure.GetCount()))) --could use seg+1
        structure.LocalWiggleSelected(1)
        selection.DeselectAll()
    end)
    table.insert(actionDescription, "Local Wiggle Selected inspired by BWP")

    table.insert(
        performAction, 
        function()
            for i=1,30 do
            if structure.InsertResidue(
                math.random(1,structure.GetCount()) --start at 1 for del.
                --I think the wiki is outdated;
                -- insert residue gives an error with index 0 (and count+1) now
            ) then break end
            end
            
        end
        
    )
    table.insert(actionDescription, "Try Insert residue/segment. Only works in Design puzzles.")

    table.insert(
        performAction, function() structure.DeleteCut(math.random(structure.GetCount())) end
    )
    table.insert(actionDescription, "del. cut")

    table.insert(
        performAction,function() structure.InsertCut(math.random(structure.GetCount())) end
    )
    table.insert(actionDescription, "insert cut")

    table.insert(
        performAction, function() 
            structure.DeleteResidue(math.random(2,structure.GetCount()-1)) 
            FindAllMovableSegs()
        end
    )
    table.insert(actionDescription, "delete residue. may cause Foldit crash in combination with GAB")

    table.insert(performAction,function() ui.CenterViewport() end)
    table.insert(actionDescription, "center view")

    --insert actions you want included by default above this line    

    performAction[#performAction+1]=function() -- +1]=function()
        puzzle.StartOver()
    end
    actionDescription[#actionDescription+1]="reset puzzle. may be necessary for multi-start puzzles. doesn't exit evolver mode like manual reset does. "


    performAction[#performAction+1]=function()
        selection.SelectAll()
        structure.SetSecondaryStructureSelected("a") --auto
        selection.DeselectAll()
    end
    actionDescription[#actionDescription+1]="auto secondary structure. won't affect score in this script, just human readability and maybe info for other scripts"

    performAction[#actionDescription+1]=function() --interchangeable here
        --    Set segments secondary structure. Valid values are e=sheet, h=helix, l=loop, m=molecule, a=auto. 
        local struct={[1]="e",[2]="h",[3]="l",[4]="m"}
        structure.SetSecondaryStructure(math.random(1,structure.GetCount()), struct[math.random(1,#struct)])
    end
    actionDescription[#actionDescription+1]="random secondary structure"
    --won't affect score until idealSS

    --end import


    ---------
    --insert new actions here before counting them --jon
    NumberOfActions=#performAction+1 --jon

    save.Quicksave(9)
    print("debug actions")
    for i=26,#performAction do --1 to skip mutate
        save.Quickload(9)
        starttime=os.clock()
        startscore=current.GetEnergyScore()
        print("debug action "..i..", "..actionDescription[i])
        performAction[i]()
        print("yield per sec "..(current.GetEnergyScore()-startscore)/(os.clock()-starttime+1))
    end
    
end
initializeActions()
----------------
pokemons={}
for i=1,4 do
    local pokemon={layers={},score=0}  --"ogres are made of layers"

    function newNeuron()
        local neuron={
            dendrites={math.random(-10,10)/10,math.random(-10,10)/10,math.random(-10,10)/10}
            --weights (dentrites getting inputs from prev. neurons)
            -- are factors to have a weighted importance
            --for instance, if you're guessing the total weight of 2 elephants and 2 insects
            --the number of elephants will be far more important
            ,
            bias=math.random(-10,10)/10--can exceed
            --bias in this case is like a T/F threshold. <50% on exam = F, you don't pass at all. 
            --some professors curve grades based on overall class grades
            ,
            axon=0 --called neuron Value by techies. means neuron output
        }
        --print("neuron axon "..neuron.axon)
        return neuron
    end

    layer={{axon=1},{axon=0},{axon=0}} --input layer, true, false
    print("input neuron axon "..layer[1].axon)
    table.insert(pokemon.layers,layer)

    layer={} --new layer
    --a Hidden Layer
    --for XOR problem, set #neurons to 2
    -- https://miro.medium.com/max/1346/1*bRoaMcjiD4yRjgfr2QGZcA.jpeg
    for i=1,2 do
        local neuron=newNeuron()
        --print("my neuron "..neuron)
        table.insert(layer,neuron)
    end

    print("done inserting neurons into first hidden")

    table.insert(pokemon.layers,layer)

    layer={} --new layer
    --output layer
    for i=1,1 do
        local neuron=newNeuron()
        table.insert(layer,neuron)
    end
    table.insert(pokemon.layers,layer)

    table.insert(pokemons,pokemon)
    
end
gen=0
lastOutputTan=2
while true do
gen=gen+1
print("new gen "..gen)
for i=1,#pokemons do
    starttime=os.clock()
    --creditbest.Restore()
    band.DeleteAll()
    behavior.SetFiltersDisabled(false)
    startscore=current.GetEnergyScore()
    --puzzle.StartOver()
    --puzzle.StartOver() --if multistart

    for iAttack=1,6 do
    selection.DeselectAll()
    --selection.SelectAll()
    selection.SelectRange(math.random(structure.GetCount()-3),math.random(structure.GetCount())) 
    --hopefully ends mutable if design but sadly not linker

    --randomize inputs to test XOR
    pokemons[i].layers[1][1].axon=lastOutputTan
    pokemons[i].layers[1][2].axon=math.tanh((1+current.GetEnergyScore())/2) --math.random(0,1)
    pokemons[i].layers[1][3].axon=behavior.GetClashImportance() --math.random(0,1)
    
    --skip activation of first layer (input layer)
    for iLayer=2,#pokemons[i].layers do
        print("gen "..gen..", pokemon #"..i..", layer "..iLayer)
        --print("layers is "..pokemons[i].layers)
        print("layer length "..#pokemons[i].layers[iLayer])
        for iNeuron=1,#pokemons[i].layers[iLayer] do
            --"inputs go in times weights, summate, add a bias activate" --s. raval
            
            sum=0
            for iPrevNeuron=1,#pokemons[i].layers[iLayer-1] do --previous neurons
                local input=pokemons[i].layers[iLayer-1][iPrevNeuron].axon
                local dendrite=pokemons[i].layers[iLayer][iNeuron].dendrites[iPrevNeuron]
                print("input "..input..", neuron weight "..dendrite)
                sum=sum+input*dendrite
                --input times weight of connection
            end
            print("sum "..sum)
            --"inputs go in times weights, get sums" -s. raval

            print("neuron bias "..pokemons[i].layers[iLayer][iNeuron].bias)
            
            local axon=sum+pokemons[i].layers[iLayer][iNeuron].bias
            --most people add bias instead of subtract bias but maybe it's easier visualizing 
            -- subtracting bias, so you can view the bias as a threshold, then you can write
            -- if axon<=bias instead of axon<=.5
            -- or something like axon<=threshold

            --"pass that **** [stuff] to my sigmoid function" -s. raval

            axon=math.tanh(axon)
            
            --[[
            --ReLU activation function, not really a sigmoid function like tangent
            if axon <=0 then --.5 then
                --axon=0 --ReLU, rectified learning unit. dying ReLU
                --  graph: __/
                aloha=.2 --alpha
                axon=aloha*axon --leaky relu

            end
            ]]--
            pokemons[i].layers[iLayer][iNeuron].axon=axon
        end
    end

    local brainOutput=pokemons[i].layers[#pokemons[i].layers][1].axon
    print("brainOutput "..brainOutput)

    --print(#performAction)
    lastOutputTan=(math.tanh(brainOutput)+1)/2  --0 to 1
    print("output tan "..lastOutputTan)
    choice=math.floor((#performAction+.49)*lastOutputTan)
    print(actionDescription[choice])
    
    performAction[choice]()
     
    --structure.WiggleAll(1) --debug
    end --iAttack

    komi=i--*6.5 --komidashi for playing 2nd

    function orFunc(a,b) return math.max(1,a+b) end
    function andFunc(a,b) return a*b end
    function notFunc(a) return 1-a end

    -- https://miro.medium.com/max/1346/1*bRoaMcjiD4yRjgfr2QGZcA.jpeg
    xor= andFunc(
        notFunc(andFunc(pokemons[i].layers[1][1].axon, pokemons[i].layers[1][2].axon)),
        orFunc(pokemons[i].layers[1][1].axon, pokemons[i].layers[1][2].axon)
    )

    improv=(current.GetEnergyScore()-startscore)/(os.clock()-starttime+1)
    --alpha for score rectifying, eg. 0.1
    pokemons[i].score= math.max(0.0*improv,improv)--+komi -- -math.abs(error)
    --[[
    behavior.SetClashImportance(
        math.min(1,math.max(0,(pokemons[i].score+100)/100)) --for visual
    )
    ]]--
    print("xor "..xor..", score "..pokemons[i].score..", 0 is best")
end
weakest=1
strongest=1
runnerup=1 --2nd best
for i=2,#pokemons do
    if pokemons[i].score<pokemons[weakest].score then 
        weakest=i
    end
    if pokemons[i].score>pokemons[strongest].score then strongest=i 
    elseif pokemons[i].score>runnerup then
        runnerup=i
    end
end
print("weakest "..weakest..", evolving weakest carp to dragon")
i=weakest
shifu=strongest --in Kung Fu Panda, Shifu is the 2nd wisest
    shifustring="shifu: "
--skip copying of first layer (input layer)
    for iLayer=2,#pokemons[i].layers do
        print("pokemon #"..i..", layer "..iLayer)
        --print("layers is "..pokemons[i].layers)
        --print("layer length "..#pokemons[i].layers[iLayer])
        shifustring=shifustring.."\n layer "
    
        for iNeuron=1,#pokemons[i].layers[iLayer] do
            --shifu can be female, shimu means tutor's wife but gender is a hassle to code
            --plus most CandyCrush pros are female
            local shifuNeuron=pokemons[shifu].layers[iLayer][iNeuron]
            local shimuNeuron=pokemons[runnerup].layers[iLayer][iNeuron]
            noob=pokemons[i].layers[iLayer][iNeuron]
            shifustring=shifustring..", neuron: dendrites: "
            --we could do backpropagation, but that involves finding the policy gradient/slope
            for iPrevNeuron=1,#pokemons[i].layers[iLayer-1] do --previous neurons
                local shifuDendrite=shifuNeuron.dendrites[iPrevNeuron]
                local shimuDendrite=shimuNeuron.dendrites[iPrevNeuron]
                print("shifuDendrite weight "..shifuDendrite)
                shifustring=shifustring..shifuDendrite..", "
                if math.random(2)>1 then
                    allele=shifuDendrite
                else
                    allele=shimuDendrite
                end
                pokemons[i].layers[iLayer][iNeuron].dendrites[iPrevNeuron]=
                    --tryhard disciple method
                    --noob.dendrites[iPrevNeuron]+(shifuDendrite-noob.dendrites[iPrevNeuron])*2

                    --pro vs pro
                    shimuNeuron.dendrites[iPrevNeuron]
                        +(shifuDendrite-shimuNeuron.dendrites[iPrevNeuron])*2

                    --valentine method
                    --(shifuDendrite+shimuDendrite)/2

                    --other half method
                    --allele

                    +math.random(-10,10)/1000
            end

            print("shifu's orig bias "..shifuNeuron.bias) --shifu not biased against MSG
            
            shifustring=shifustring..", bias: "..shifuNeuron.bias
            local allele
            if math.random(2)>1 then
                allele=shifuNeuron.bias
            else
                allele=shimuNeuron.bias
            end
            pokemons[i].layers[iLayer][iNeuron].bias=
                --tryhard disciple method, kinda velocity gradient descent
                --(noob.bias+(shifuNeuron.bias-noob.bias)*2
                --Tutor says to chop a log, chop 2 logs
                
                --tryhard pro method, note that I don't mean tryhard in the derogutory sense
                -- but rather that imitation is a fast (albeit not as great as AlphaZero) method
                --After all, I guess it's why stories unrealistically have happy endings
                (shimuNeuron.bias+(shifuNeuron.bias-shimuNeuron.bias)*2)
                --Eg. What can Starcraft pro Scarlett do to play like #1 Serral but better?
                --Double Evo chamber or more creep tumors?
                --This method finally got the a.i. to set clash 1

                --valentine method, but kinda a social bubble stagnation
                --"2 roads diverged in a yellow wood and the a.i. car barged down the middle" -GeoHot
                --(shifuNeuron.bias+shimuNeuron.bias)/2
                
                --half of genes        
                --allele

                +math.random(-10,10)/1000 --Mozi likes precision

        end
    end
    structure.SetNote(1,shifustring)
--print("end carp to dragon?")
--sometimes get bias of -0 negative zero. but -0==0 in lua.
end

Comments

[zo3xiaJonWeinberg]

shifu:
layer , neuron: dendrites: 0.097, 0.39, 0.398, , bias: 0.106, neuron: dendrites: -0.493, -0.291, -0.896, , bias: 0.992
layer , neuron: dendrites: -1.003, 0.81, , bias: 1