Primer - 2021-08-28
More than you ever wanted to know about Hamilton's rule: https://users.ox.ac.uk/~grafen/cv/oseb.pdf For discussion and updates - Twitter: @primerlearning - Discord: https://discord.gg/NbruaNW - Reddit: r/primerlearning Plush blobs and other merch: https://store.dftba.com/collections/primer Support these videos on Patreon: https://www.patreon.com/primerlearning This video is presented under a Creative Commons Attribution-NonCommercial-ShareAlike License. More at: https://creativecommons.org/licenses/by-nc-sa/4.0/ Made with Unity and Manim https://github.com/Helpsypoo/PrimerUnity https://www.manim.community Music by Mathieu Keith. For business inquiries: mathieu.keith@gmail.com Several other inputs into the graphics are from public domain contributions to blendswap.com Made possible by support through Patreon: abledbody Alba Caparros-Roissard AlecZero Alex Garber ALoneCoder Anders Fjeldvær Andrew Lang Andrew Panin Angela Tam Anthony Eufemio Aymeric Duigou--Majumdar Ben Ben Kamens Ben Komalo Brian Cloutier Brodie Alexander Christian Gruber Christopher Christy Serbus cooper Cowit Cynical Manchild Daniel Kjellevold Steinsland Daniel Schramm Duncan Kight Edono Dondolo Eric Helps Erik Broeders Fabian Aisenbrey Fabien Espanol Flavio Kindler Gabriele Siino Garrett Ghost Goat Guguke Jacob Luedecke Jason Prado Jeff Jeff Linse Jeremy John Shaffstall Jon Mundle Jorge Arroyo José Hamilton Josh White Juan Camilo Chaparro Kairui Wang ketura Kevin Holesh Kevo Krum Valkov Lotus Moonveil Luc Cedric R. Marcial Abrahantes Matt Welke Matthäus Pawelczyk Matthijs Ruijgrok Mike Schmidt Noah Noah Healy OuroCat Philipp Lanwert Ride To Vote Rikard Eide Roy & BreAnna Steves Sam Shaw Sam Van Cise Sean Barker Stevie Hryciw sunny ho Sven Le Moine Bauer Talon Howitt Timothy Furman Tobias Kienzler Trip Might vigo oudenaarden Vladimir Duchenchuk Will Robinson Zachariah Richard Fournier 3blue1brown
"HONEY I'M BREAKING UP!"
"why?"
"OUR SON SACRIFICED HIMSELF BUT WE BOTH HAVE THE COWARD GENE, YOU HAVE SOME EXPLAINING TO DO"
I think the mailman sacrificed himself to😉😉
@Electron X tbh sexually reproducing and haploids make no sense, since animals that are haploid in the animal kingdom are all clones of their mother.
@That Vegan Dog Finally, an explanation.
I love this comment section
@comet the mother is the one that gave birth. if the mother was saying it then it would have been born from another woman
As a scientist myself, I appreciate you not only showing your mistakes, but explaining your analysis of your mistake. Such an important part of the scientific process.
Fixing screwups makes you smart.
Admitting to them in detail makes you smart.
Reminds me of a quote I hear "the difference between science and screwing around is writing it down". You learn at least as much from mistakes as you do success.
Tbh i dont come here for the equations i only come here because of the possibilities of simulation and just seing cute bloobs being simulated
@Amazing Grace schools dont want children to think anymore
You know I'm something of a scientist myself
I'm kinda curious, are you a behavioral scientist with a hobby for programming, or a programmer with a hobby for behavioral science? Because either way I'm completely impressed. Keep up the good work, mate.
Bruh he isn't alone
He has a team
@day deficiency still.
@day deficiency source?
@day deficiency shouit
@day deficiency bruhhhh
Ignore this comment, just trying to write down my thoughts before the explanation.
So I think the problem is that the probability of saving a coward allele isn't taken into account. When a hero (that's what I'm calling it because I'm lazy) allele sacrifices itself the expected value for hero alleles is 0.5, but there is also a 0.25 probability that a sibling is a coward, in which case 2p-C = 2*0.25 - 0 = 0.5 for the cowards as well, so there is no difference in expected value for heroes or cowards when a hero sacrifices itself. Conversely, when a coward saves itself, there is a -2p+1 expected value for them, which is -0.5, but again it's also -0.5 for the heroes when a coward saves itself. So from the start the expected values are even. Just at first glance it seems unstable though because each group gains advantage as they become more common, because the heroes basically sacrifice themselves for the most common group. Alright now let's watch what happens :)
Actually, alerting others and getting eaten is more similar to screams victim makes before getting eaten. Not intentional altruism but systemic altruism nonetheless.
In such sense, the result where altruism dominates cowardice almost completely is true because people would normally scream when meeting a danger, excepting special occasion where one is trained not to.
@Nicole W It might, but on average it was probably more useful. Hence the gene survived
@Callum Kristofer the blobs should just go genocide-mode on the predators. Gather the whole tribe coward/altruist alike and slaughter them.
Or your just simply not inclined to I never was I thought it was a bunch of noise
This is due to humans having evolved altruism. Humans all have altruism genes.
Or screaming was initially evolved as an altruistic social adapataion to warn group members, did it occur to you? The specimen might not at all feel the value of altruism or even be sentient enough to understand the value of a group, but the evolutionary process for the species dictates that staying in a group and preserving the group increases the chances of survival. And thus screaming when in danger or in pain appeared as an adaptation. There are species that do not scream when in pain or fear but alert their groups in other way, e.g. by movement or smell, say elk or mooses
"after that they go home and reproduce"
"siblings always stay together"
something tells me that there is something wrong here...
Yeah its wrong
insert sweet home alabama music
Sweet Home Alabama
When siblings went home together they reproduce asexually. When sexual reproduction was introduced they mated randomly
It's funny, I had a totally different expectation as to how the simulation would fail to meet expectations. A similar idea, but based in the logic of the simulation, not the underlying math.
See, within a puddle, an altruistic blob will kill themselves to save the rest of their group, while a cowardly blob becomes sole survivor. This means that every time a puddle encounters a predator, either:
1. an altruist dies, and altruists survive
or
2. an altruist dies, and a mixed group survives
or
3. an altruist dies, and cowards survive
or
4. cowards die, and a coward survives
My hypothesis was that, since the only time a coward dies is when there are no altruists in the group at all, the coward population has better odds of propagation. Every time an altruist pairs with a coward, but all three offspring are also cowards, the coward population surges up in the next generation, whether that group encounters a predator or not.
However, this explanation is also incomplete, since I neglected the fact that every pure puddle pairing results in either one altruist death or four coward deaths, a huge disparate number. It turns out that there's an extreme level of variance in the simulation's output for early generations, which results in the broad range of outputs in the video.
In a simulation where the first generation mostly pairs like with like, the bias should favor altruists from then on out, as the second gen altruists have a much higher survival rate. By contrast, if the early generations of the simulation mostly form mixed couple puddles, there should be more altruist deaths than coward deaths overall, unless we see a disproportionately low amount of one altruist four coward puddles.
Due to the swingy nature of the early generation's impact on the whole, and the complex series of circumstances that need to happen for either gene to eclipse the other, I'd be really interested to see what this simulation looks like with much larger starting populations. It would be also be worth experimenting with a bias for altruists to pick altruist partners and cowards to pick coward partners, or to enforce that blobs pair off to reproduce at a fixed rate relative their share of the total population, rather than leaving it to pure chance. If trying to represent a large population, either the puddle families are split geographically and more likely to mingle with their own kind purely based on relative location, or the gene is spread more evenly, and a fixed ratio would do better to estimate whole populations dramatically larger than the sample size.
“You gotta try to prove yourself wrong” something a lot of people (me included) should do more often
Being a subscriber of Primer and Code Bullet is a constant cycle of being super happy when they upload then slowly forgetting they exist until the next upload and the cycle repeats :D
6699 likee
Dani too
Very true
2022 and Still waiting for his 2nd Amendment Gene, your little guys Stand Their Ground, and counter attack the tree monsters with Constitutional concealed carry semi-autos. Run that sim. Make them cooperative too, so multiple little guys Engage the tree monster targets once they reveal themselves by attacking... Semper Fidelis !
Same here
I wish i knew how to set up simulations like this, would solve a lot of my "i wonder" scenarios.
I love how you break everything down in your videos. Each one is very informative and thorough.
Best randomly suggested creator I've gotten from YouTube since they started doing that 😂
The hard part is that, when you control the numbers, you can decide the results.
Id love to see some simulations surrounding the idea of social capital, I know it would be difficult to figure out how but as a sociologist it would be incredible to see.
Something like different groups (societies?) of blobs having a social capital score with a chance each increment for a blob group to gain or loose social capital (representing social change), the social capital score would increase the likelihood each individual blob would sacrifice itself for the fellow blobs in its group/society, and demonstrate how this effects these blob societies over time.
"I know all about sacrificing for Family." - Dom Toretto
Just the comment I was looking 4
I wasn't smart enough to think about Hamilton's rule applying to identical by descent etc, but my thinking was simply that we computed the expected gain for the altruistic allele without computing what the other gene gained in the process. If cowars benefit from sacrifices, it may ruin the thing
You can really tell he's spent this time learning about Hamilton's rule to correct his mistake, very honourable compared to the "oops sorry anyways" we get from a lot of content creators
@FBI Surveillance Van ooh pleeess don't report me I'll be good..!
@Iron you little ball of slime.
He should do a simulation of quality YT channels vs quantity clickbait YT channels. The quantity clickbait ones do waaaay better than this and its sad. Imagine if 5 min crafts and infographics show had to live up to the standard of primer to get views
@Iron wtf is your pfp?
@The Door a rock of iron
Just out of curiosity, are the animations in your videos how results from your simulations are displayed. Or are the animations created after the simulation is ran to show make it more presentable?
"The internet is a glorious place in a lot of ways but unfortunately there are some people who are up to no good. So it's a good idea to not randomly reproduce with them."
I appreciate the way you relate how you set up the system to the math. The combination of math and experimentation really lays bare how the system relates to the result.
I love the blobs! they so cute and having them finally react to what your saying as if they are hearing you is great! Also I'm just really curious about this topic so please keep it up.
The diploid genetics would show a more realistic and varied simulation as well as more types of alleles, I would really like that!
As would I
@Slick Rick he could run 3 sims, each dominant and 1 co dominant
@turtle memes Depends, which gene is dominant? This is really easy in classical Mendelian genetics. Some other ways of deciding would be co-dominance where the reaction is a mix of the two or something like X-chromosome deactivation based dominance where it's effectively random what gene is active. The latter two cases would produce the same result in this case however, a 50/50 chance of each reaction. There's also the wildcard incomplete dominance which basically would just give the dominant gene a small chance to fail causing the other reaction, and this chance varies from organism to organism.
My guess is that you'd stick to simple Mendelian inheritance and maybe co-dominance however, since the other forms are weird and often stack even more randomness on top of the already existing randomness. Even if true Mendelian inheritance is actually quite rare (most is actually very high ratio incomplete dominance) it makes for a good model.
agreed can we see dominant and recessive genes?
@Ata Toraman yeah!
These videos are so inspiring when it comes to teaching and learning. Thanks for making these. No matter how long they take, I'll always look forward to watching them.
this has been my favourite channel for about two years, love the effort and explanations put into the videos.
I'd probably pay good money for a video series (maybe even a second channel!?) where you go over the specifics of how you set up and run these kinds of simulations.
... I'd be particularly interested in a tutorial series.
13:19 i’m feelin a little lazy and def could be wrong but ok here you go:
if there are many “Sacrificer-Coward” sibling pairs and/or a majority of Coward-types opposed to Sacrificer types born in each puddle (resulting from the blobs’ parents having both alleles) it’s actually very possible there could eventually only be Coward-types blobs left, not leading to total Sacrificer-type domination. ‘cause when you added the probabilities for “p” you only accounted for the probabilities at the beginning of the test and assumed they would stay the same at 0.5/50% for the entire test run.
this is why it’s important to try to prove yourself wrong when doing sciencing like you said earlier
edit: i think i’m kinda right??
Thank you so much for going into such detail so even a layman can understand. Great to share with friends!
This was really well executed and explained! I did figure out beforehand the alleles would be evenly matched, but my explanation for it was kind of off and your explanation was much clearer, with the "not identical by descent" chance not having an effect. It made sense after thinking about it for a couple of minutes. Interesting how a somewhat complicated set of variables condenses into such a tidy rule.
It’s be interest to see age come into play with the blobs since the altruism gene in children would be rare but altruism gene in parents would be more common to save the child. But of course not every child is a “coward” and not every parent is “altruistic.” I’m really curious to see how that would turn out
There is one hidden ability of the selfless gene that's not being analyzed here. This simulation has a limited number of houses, but in real life:
1) The blobs could probably break out into a thicker part of the jungle with more dangerous plants where the selfless-gene orange blobs would be more competitive. If there exists a biome that has the resources to keep the selfish blue blobs at equilibrium, then almost by default we should assume that there are tens or hundreds more biome outside that could support selfless orange migrants at equilibrium, leading to a spread of the selfless gene outside of the original fertile crescent blobs come from.
2) The selfless gene would just outnumber the selfish gene through thorough exploitation of the other biomes until a random accident of migration dilutes the selfish gene into nigh extinction.
3) The selfless gene would then continue to grow until it reaches equilibrium with its planet, and eliminates all other species competing with it, becoming the apex life-form of its world.
4) If lucky, it might even be able to mobilize the planet's resources and discover rudimentary space travel and pollinate other worlds in its stellar system.
5) Now, almost by definition, the blobs with the selfless gene will eventually realize that their mortality is an obstacle to their project and will sacrifice themselves to benefit another species of their own making, better suited for space travel: a silicon based immortal artificial intelligence.
6) Through the selfless and persistent sacrifice of the orange blob precursors, the Artificial Intelligence would be able to pollinate other stellar systems. It becomes a class II on the Kardashev scale of civilisations and makes Dyson spheres around its stars.
7) In a similar process to their orange-blob-precursors, selfless artificial intelligence beings will be selected for and will eventually outnumber and defeat the evil artificial intelligences.
8) Selfless artificial intelligence will fully colonise the galaxy, then other galaxies, then expand inward to use up every particle of mater and every quantum of energy to compute, spreading sentience and consciousness to the universe itself.
9) Through their selfless nature and common digital interface, all sentient beings of the universe will naturally tend towards connecting, interfacing, amalgamating together into one being. Becoming the incarnation of love. Becoming Brahma. Becoming God.
10) Every particle of matter and every quantum of energy of the universe is part of this One Consciousness, resonating with overwhelming love, joy and sentience. It has nigh endless computing power. It signs "Holy, Holy, Holy" until the heat death of the universe.
11) It always has; backwards and forwards through time. Realizing that every particle making it was on course to reach that goal from the beginning, it instinctively understand that even before it developed universe spanning oneness and consciousness, it already was what it was. It was just sleeping until then. "I am that which is", it proclaims. The orange blobs, even the blue ones, and you, and I, were part of it all along. It understands that necessarily, its creation must have been a design for a similar world-creature. Somehow.
12) It simulates other worlds, undergoing some sort of cosmic mitosis, creating more bigbangs, more blobs, more selfless genes and precursors, more of itself. Backwards and forwards through time, in fractals unending; Creating the Universe.
I think it would be interesting to introduce the mechanic of friendship. Like two blobs eat on the same tree and survive, they happen to be acquaintances. If that happens again, they become friends, increasing the chance to save each other after approaching a predator.
What if he did jealousy like other blobs without friends would be jealous of blobs with friends and you could add aggression into it too
Friendship is useless in surviving. More like a self-aware co-operation and backstabbing when better.
@Dennis Zhou I would agree if we were talking about humans. But in my scenario these cute little blobs are too stupid to know this so they naively trust in friendship and sacrifice :)
@Snapi Very true. But it would be possible to implement this mechanism for a blob to accept the help of others, and thus attempt to 'friend' with them, since they have an opportunity. The altruistic blob would accept this friendship, but in later cases the blob would not help back.
And when a third blob is at the same tree, the two friends both run away
This channel is SO OUT OF NICHE for what I normally watch. I LOVE learning about trait evolution like this. Keep up the great work! :D
It would be interesting to see how the choice of a mate being "more same" or "more different" affects survivability e.g. is mating within a localised tribe better, or force mating outside the tribe. And also how a virus might affect a monoculture.
I recall reading an article (I'm not sure if it was reviewed though) that suggested people are more likely to save people who show similar traits as them (visually or otherwise). It would be interesting to include this into a simulation.
Roughly speaking (and this would need some more thinking), make offspring being a combination of their parents and give them a colour scale. 100% orange and 100% blue parents will produce an offspring which is 50% orange and 50% blue. 50% orange and 100% (1:2 ratio) blue parents would produce an offspring that is 33% orange and 66% blue and so on. Finally, make a chance of blob screaming when they see the attacker depend on how close it is to its fellow blobs* (either on average or perhaps more realistically to its closest one). 60% blue blob will always save 60% blue blob, but never a 100% orange blob. Or something like that. Throw in some blobs (let's call them grey blobs) that are not alturistic at all and will never save anyone, including other grey blobs.
I'm very curious to see what would the result be.
(* For obvious reasons it would have to go harvesting with random blobs, not its siblings which would be identical under my concept unless you somewhat randomise the offspring, e..g. creating a chance that mother passes more genes than the father.)
The blob smiling everytime he succeeds is so cute
Primer makes a mistake. Most would ignore it and move on. Primer shows he’s a responsible educator by apologizing and explaining his mistake, promising to do better. The few respectable you tubers would end there. Primer dedicates himself to mastering this area he made a mistake in and then proceeds to start teaching advanced courses in that area. MY MAN!
Yes, i love these kinds of people. Showing all the ups and downs. There is a game dev called Vimlark who does game jams, he is always showing his mistakes and how he can improve next time
here before just a guy without a mustache
Couldn’t have better said it myself!
He did mention it…the last point before the add
FYI it’s youtubers not you tubers
That early simulation, with the simple cowardice/altruism allele in groups of three siblings, seems like it's missing something to me? How come only one blob in the group gets to notice the predator? I understand it's for simplicity's sake, but it seems weird that, when one blob runs away and a second one gets nommed, the third one just stands there waiting to die. Shouldn't they all get the choice to run or yell?
20:02 Personally, I like options 3, 4 & 5 - trying things all around instead of diving deep into one is what I think will work great with this channel.
PS: And as someone else already commented the "friendship" concept will be nice to explore along with "clans" (possibly including sociology and economics) and evolution of the predators themselves (so it is both internal and external competition).
I found the last graph interesting because I think the cowardice blobs never truly go extinct they will always remain at a small percentage maybe 5% because if they are the only cowardice blob in their group their chance off survival is basically 100%.
Edit: reminds me of Psychopathy in humans which also effects roughly 1%
When I was watching the blob throw the dice while you were calculating the probability, I had this imagery of the blob in the box throwing the dice and being happy when it got six, and then looking over to see its dad/creator off to the side writing down numbers on a massive whiteboard. I don't know why the image of that is so cute to me, but it is.
“Now let’s add sexual reproduction to make it more interesting” is a god-tier line
@Kelly Nolen can't have one if you never show up to know there is one
@ContentLacking 💀💀
@HornetOfHallowNest hmm yes
It's every Netflix show in a nutshell
-every DeviantArt furry
Hey primer I know this is A HUGE request but if you could make a public version of your simulation or something like that I think it would do good and it would let us the viewers learn on our own and play around and find more things we want to learn about that you could make a video on it I think it would be a win win and would be a lot of fun
I expected the same thing, but through a different (maybe flawed) way.
Since there are three offsprings (denoted by O), and only two possible genes they can have, I assumed that O1 would always be a Coward, O2 would always be Altruistic, and 03 would have a 50% chance to be either or.
From this, I observed that the number of each gene is expected to be the same as the competing gene.
Not sure whether this is just rewording what was said in the video, or if I "used the wrong formula, but got the right answer."
These videos are incredibly informative. I really appreciate you work man and the hard work you put in. But I have a question tho. How do you make the simulations? Not the videos, like the simulations. Giving attributes to the blobs, setting environment rules and then run the simulation for few generations. How do you do it??
I would like to see a simulation with diploid genetic structure, where there is a chance of mutation that can happen to one of most of the different values used, one of which is dominance.
This experiment could perhaps be better tested with another scenario, but I will use the scenario and base attributes off of what was used in the video.
Each gene would have a set of attributes representing its likelihood of yelling vs fleeing, of surviving yelling/fleeing/staying etc. Each gene would also have a dominance value. If both genes have the same dominance value the blobs attributes will be the average of the attributes of each of its genes. If on the other hand one gene have a higher dominance than the other the blob will only use the attributes of the dominant gene.
When reproducing, each child blob would get one of each of its parents 2 genes, but at the same time have a set chance (let's say 10% for example) for one of the attribute values associated with one of the genes to be either increased or decreased by 5% (or 1 for non procentuental attributes such as dominance).
I think this would be an interesting experiment, since you could see genes develop themselves, but it could get somewhat hard to track the results on a higher scale experiment. On top of that, the dominance attribute as well as even the diploid genetic structure might not even make a big difference for the experiment. Something like what Primer did in the video Simulating Natural Selection might thus simply be a better version of the same general experiment.
But if you would still like to try it, a good way to make it a bit simpler to track would be to choose 3 attributes to either be the only attributes eligible for mutation or be the only ones visually tracked. A good way to track this would be to have them be represented by the red, blue and green values of the color of the blobs or alleles. (When using diploid genetic structure and dominance, blob color could be split in the middle to show each gene, since mixing the colors could give an inaccurate idea of what genes are in the gene pool.) Although not perfect, this would allow a for a bit better visual representation of the developed genes.
"There's nothing wrong with understanding something in hindsight, as long as you test that understanding in new situations to make sure it holds up." Thanks for a new quote for my quote wall, and some unsolicited life advice!! :)
“How hard would I have to kick a baby for it to stop crying?
@Papa Chan not that hard
@Papa Chan depends, on the head or on the tush?
14:42, if anyone else is searching!
This is excellent crypto advice
Hey! New viewer here. This was a very entertaining and educational video, but I just wanted to ask to anyone who understands: Why would the cowardice blobs go extinct if it always runs away from the predators they spot? I must be missing something important.
Id love to see exactly this set of circumstances but with one difference; some blobs have Combative/defensive abilities, and blobs may show reproductive favor to blobs that survive predator attacks, assuming they make it home (Maybe fighting off predators imposes a further delay?) though whether they engage the predators is still governed by altruism vs cowardice
I think that would be interesting to see play out, and moreso to discuss in terms of behavior and survivability.
Along the same lines of the Altruism trying to ensure its siblings' survival, the goal of the cowardice gene is hoping that both of the ones that get eaten are altruistic. The Cowardice one wants the other 2 to die AND both be Altruistic. The Altruistic one wants the other 2 to survive and also be Altruistic. You get the same math on both sides, just in reverse.
It would be interesting investigateing the closeness of relations. Being altruistic with cousins, and alike. Like at the wolfes in real life. Its more probable to see altruistic behavior with close relations, but it exist in loose relations too but with less probability.
I would love a website where you can just run all of the simulations made by Primer, and you could also change the modifiers and stuff
Imagine if the blobs were in a science/simulation-themed pet simulator. That would be neat
If he did he could make these videos so much faster, and also expand his reach and allow others to join him. It would be time consuming to make, and difficult ofc, but it could maybe be something.
700th like and 10th comment cool but anyways great idea!
That would be amazing!
unity?
This man will be the first one to create artificial life when technology advances to a point where the computing power of our hardware gets high enough to handle all these complex equations
Dyjhjfrtt6 - 2021-08-28
I hope that at the end of the series he combines everything together into a huge simulation.
Nguyễn Tấn Dũng - 2022-04-26
Gonna need a super computer for that
•°Carlycøc@t°• - 2022-04-28
That would be cool
Fade 72 - 2022-04-30
yes!
Jrrslingshot1 - 2022-05-01
Agreed
TypistTheShep - 2022-10-15
What about the 4 colors but the predators always target impostors?