Archive for category Evolution


This post turned out ramblier than expected. Sorry about that: it seems to be happening more and more lately. My forum posts tend to be a bit more coherent.

Alright, let’s present some more evidence for evolution: in this case, the evidence that Darwin used to convince his peers. Back in the 19th century, there was a very sparse fossil record, no understanding of genetics, and organisms changing over time hadn’t even been observed, yet Evolution still had enough evidence behind it to convince the scientific community and smack down the existing dominant theory (Intelligent Design: 150 years out of date).

What made up the shortfall in other areas, and what Darwin spent much of his book outlining, was biogeography: the relationship between biological life forms and the area’s they inhabit. Explorers were in vogue at the time, so there was a lot of data available on the distribution of various types of creatures across the globe, and of course Darwin got the chance to witness it first hand in the form of the Galapagos finches (Dude spent 7 years of his life studying oysters, but somehow it’s the few weeks watching finches that everyone remembers him for).

What Darwin noted was the fact that, as geological separation increased, so did biological separation. The animals close to each other would be more similar than the animals separated by hundreds of miles. Animals separated by water or desert or mountain ranges would diverge even more extremely.

Australia’s marsupials are the boring textbook example of this, and everyone’s heard that one before, so to mix things up let’s go for a more interesting and complicated example. Besides, small furry mammals are overrated: there are equally adorable creatures amongst the other families.

Who’s an adorable blind fishy? You are! Yes you are!

Some fairly recent DNA analysis determined that the closest relative of a species of blind Australian cave fish isn’t another type of Australian cave fish at all: it’s a species of (equally blind) cave fish found in Madagascar, on the opposite side of the indian ocean.

At first glance, this hardly seems like evidence for evolution: quite the opposite, in fact. These fish aren’t built for travelling: swimming across the Indian ocean isn’t a simple proposition when you’re less than 10cm long and blind, not to mention adapted for freshwater. So how do two closely-related species of effectively-immobile organisms end up on opposite sides of the ocean?

That’s where geography comes in: specifically, plate tectonics.

I assume we’re all familiar with Gondwanaland, the supercontinent that split apart in the cretaceous? As you can see by this map, Australia and Madagascar were connected by Antarctica, implying that the common ancestor of these fish lived at least 100 million years ago. This matches up with a load of other biological evidence for the Gondwanaland split: the few marsupials that survived the rise of placental mammals outside Australia are all on other subcontinents of Gondwanaland, the Jurrasic-era dinosaur species that lived in South America are identical to those in Africa and Antarctica. On a less charismatic scale the pattern still holds true: all of Madagascar’s freshwater fish groups, exhibit relationship patterns related to the breakup of Gondwana (some are related to groups in India/Sri Lanka, and others to groups in Australia) including our cave fish.

It’s this culmination of evidence that makes Evolution such a certain thing, but also makes it so hard to convince denialists of its veracity. The evidence for evolution often can’t be summed up with soundbytes or images: with moon-landing denialists you can show off photos from the lunar reconnaissance orbiter, with cryptozoologists you can point out that the requirement for a stable population means at least 100 sasquatch individuals wandering the mountains. There’s very little like this for evolution, because the evidence is strongest when taken next to all the other evidence, giving denialists an easy out: by picking holes in a single element at a time, they never have to confront the overwhelming mountains of evidence behind them.

HERV’s are one of the most concise and definative arguments for evolution I’ve found, and even they depend on a pattern, rather than an instance. Fossils like Archae and Tiktaalik help, but are also easy to dismiss: “there are no transitional fossils” makes for a better soundbite than “the term is misleading since all fossils are transitional to one extent or another, but several fossils display transitional features including…”.

Screw it, here’s a chainsaw rover:

And you thought the Terminator was scary

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Detecting Design

Okay, well for the life of me I couldn’t figure out what to write yesterday. Tried doing a Junk DNA post, but others have done it better (while talking about a different subject to boot). So I’ll need to come up with something different.

… how about this? I mentioned briefly in a footnote a while back the differences between top-down design and bottom-up evolution.

Believers in Intelligent Design (“It’s creationism but SCIENCEY!”) have a small number of suggested methods for ‘detecting’ design. Dembski’s filter tries to eliminate natural occurances, Behe’s irreducable complexity sets specifications for structures to meet to be the product of design, and a variety of Appeals To Common Sense that don’t really provide anything worth mentioning… but the one thing they have in common is that they all return “true” when applied to biological life.

Interestingly, mainstream science also has a number of methods for detecting, not design, but the results of design. Archeologists look for tool-marks and compare them to tools the humans of the time were known to be using, and SETI looks for mathematical regularities in radio signals known to be produced by the devices of our technological civilisations, etc. Interestingly, both of these examples are cited by IDists as evidence that meanstream science believes detecting design is possible, despite the fact that neither of them returns true when applied to biological life: DNA synthesisers don’t leave ‘tool marks’, and known mathematical regularities within organic life (for example, bilateral symmetry) are more simply explicable as the result of optimisation, not of design. Occams Razor wins again.

So why do the IDists methods return true? Partly at least this seems to be the result of confirmation bias. The Intelligent Design movement is a direct descendant of the religous creationism movements, so the design detection methods were themselves written people with the intention of confirming what they already believed. It’s no surprise that they would return the value their authors wanted them to.

But that’s not entirely it: the authors might want their algorithms to return true, but that doesn’t change the fact that the algorithms themselves do return true. So what are they detecting?

The difference seems to be that mainstream science looks for examples of human, or at least physical, design. The IDists look for any type of design, and they find it.

This isn’t actually a false positive: progressive optimisation via natural selection is a type of design. But it’s a natural, unguided form of design. Richard Dawkins dubbed it the “blind watchmaker”.

I’ll approach this with an example. Since I’ve already written about Behe’s abuse of Mullerian Interlocking Complexity, here’s William Dembski’s Explainitory Filter, in his own words:

Given something we think might be designed, we refer it to the filter. If it successfully passes all three stages of the filter, then we are warranted asserting it is designed. Roughly speaking the filter asks three questions and in the following order: (1) Does a law explain it? (2) Does chance explain it? (3) Does design explain it?

Dembski then provides an example from American law: Nicholas Caputo, a democratic senator, put the democrats in first place on the ballot papers in 40 out of 41 instances. This provides a statistical example for Dembski’s filter:

Unbeknownst to Caputo, he was not employing a reliable random process to determine ballot order. Caputo was in the position of someone who thinks she is flipping a fair coin when in fact she is flipping a double-headed coin. Just as flipping a double-headed coin is going to yield a long string of heads, so Caputo, using his faulty method for ballot selection, generated a long string of Democrats coming out on top.

In selecting the order of political parties on the state ballot, Caputo employed a reliable random process that did not favor one political party over another. The fact that the Democrats came out on top 40 out of 41 times was simply a fluke. It occurred by chance.

Caputo, knowing full well what he was doing and intending to aid his own political party, purposely rigged the ballot line selection process so that the Democrats would consistently come out on top. In short, Caputo cheated.


Naturally, the filter (and the court) disregard the first two options and rule in favor of the third.

Now let’s apply Dembski’s filter to biological life. If you read the source article linked above, and after you’ve taken an painkiller to get over the fallacy-induced headache, you’ll note that Dembski never really applies it to life himself. Instead, he cites a variety of scientific hypotheses that “get around” the necessity of a conclusion of design when applied to biological life. (most of which are actually more related to Abiogenesis than Evolution, but he disparagingly mentions Darwin (with bonus points for the shoutout to YEC’s)* so I’m going to use modern life).

So let’s find something small and cute to apply Dembski’s filter too. I know: say hi everyone!


The appearance of adorable salamanders is something that always happens, given a world like ours and 4.5 billion years of time. Uh, no. Not that we can re-run the simulation to find out, but I think we can rule out axolotyls as a physical law of the universe.

This species formed by random chance: some completely different animal, like an elephant, just up and gave birth to the first axolotyl by means of an extremely unlike complete-genome mutation. I think we can eliminate chance as well.

Ergo: Dembski’s filter concludes the axolotyl was designed.

But… at this point, Intelligent Designists smugly call it quits. “It was designed, musta had a designer.” But how was it designed? What was the ‘designer’ looking for in an axolotyl? IDists don’t look this far: they’ll tell you it’s about detecting the presense of the designer, not analysing it’s motives.

But careful examination of the axolotyls features (of any feature of any species on earth, really) reveals what the “designer” was after: ability to make new axylotyls. From the display tentacles to the body structure, all the features are either oriented around the continuation of the species, or just along for the ride: remnants of old features that were also oriented around the continuation of the species. This heavily implies the Bottom-up design that the natural process of evolution produces, not the Top-down stuff we associate with human/intelligent design.

That confirms what biologists already knew via other lines of evidence: that the “designer” was just mutation and natural selection. It’s a shame the IDists always stop looking just before realising this conclusion.


*footnote: Dembski implying Darwin came up with the age of the earth. Charles Lyell’s remains must be generating quite a bit of torque by now (hey look, an alternative energy source!).

Thus Darwin, to prevent the probabilities from getting too small, had to give himself more time for variation and selection to take effect than many of his contemporaries were willing to grant (cf. Lord Kelvin, who as the leading physicist in Darwin’s day estimated the age of the earth at 100 million years, even though Darwin regarded this age as too low to be consonant with his theory).

“In the future, politics will be redundant. World leaders will be ultimately decided by whoever can genetically engineer the cutest species of axolotyl to use in their campaign ads.”

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Bill Nye is not appropriate for Creationist Blood Pressure

Recently, Bill Nye [the science guy] produced a video called “creationism is not appropriate for children”. It’s fairly short and he doesn’t go into much detail: mostly a bunch of assertions on Bill Nye [the science guy]’s part. From what I’ve seen it shouldn’t be difficult to support those assertions with evidence (they’re nothing particularly controversial), but Bill Nye [the science guy] doesn’t bother: he simply presents them as is. Really, it’s more a presentation of an opinion, rather than a particularly detailed or thorough takedown of creationism.

Now I’m Australian, so until recently I’d never heard of Bill Nye [the science guy] (Note: I have been assured that “the science guy” is a mandatory part of his name and that if you don’t use it he magically scientifically appears and beats you over the head with a Bunsen burner). I understand he’s a science communicator and used to have his own TV show, but the remainder of my understanding of who he is and what he does comes almost entirely from Randall Munroe.

So what I find interesting about this case isn’t Bill Nye [the science guy]’s opinions on creationism. I don’t know the guy, and his opinions are really pretty standard stuff amongst people with any understanding of science: the video itself is about as controversial as a NASA engineer saying the moon-landing hoaxers are a bunch of loons. What I find interesting has been the denialsphere’s reaction to Bill Nye [the science guy]’s opinions on creationism. It seems like every creationist of note suddenly went critical.

There’s enough atomic energy stored in creationists to melt the crust off the earth. (it’s funny ’cause it’s true)

Various creoblogs have been tearing ineffectively at him, and there have been more than a few video responses, including white-background parody’s from groups as well known in the misinformation sphere as Answers In Genesis.

“… the complete lack of a genetic mechanism that allows organisms to gain information”? If this blog was a drinking game, I’d be insisting everybody take a shot right now.

So what I want to know is: why is it that this particular video of a guy on a white background garnered such a reaction? There are plenty of more vehement, more eloquent, more thorough and more fact-oriented video’s on YouTube condemning creationism, some of them from well known and popular people. But it’s Bill Nye [the science guy] that gets all this attention. Why?

It can’t be the format: a YouTube interview is hardly anything new.

I think it might be partly the content. Bill Nye [the science guy] provides an emotional argument: a plea to get back to real science in America. This is in many ways more persuasive than a step-wise, fact-based argument… but it’s also the creationist community’s home turf, which allows them to engage on their own terms. Since Bill Nye [the science guy] didn’t provide immediate facts to back up his assertions, the creationist responses can be simple denial: they are under no burden to prove otherwise, and the audience for all their exposure to “both sides of the argument” is no more informed than they were before.

Mainly, though I think it’s a matter of the source. Bill Nye [the science guy] is well known, and not in the same way that evolutionary scientists like Dawkins are well known. He is a scientist, yes. But far more importantly to the denialists, he’s a TV personality.

Bill Nye [the science guy] isn’t an authority on scientific matters: one of the “experts”. Denialists have done a fine job of slandering the very concept of expertise over the years, to the point where amongst their audience scientific experts are less trusted than weathermen (and in the case of climate change, I mean that literally). But Bill Nye [the science guy] is more than just one of the faceless experts: he’s someone that introduced people to science, showing them how it worked and that it worked. He showed people the side of science that wasn’t the dry academia we’d seen in school. It’s easy to accuse a faceless consensus of experts of lying to you, but Bill Nye was someone people came to know and trust. And that, I think, is why the denialists are so apoplectic about Nye: they have plenty of experience denying facts, but it’s harder to combat the opinions of someone your audience knows and trusts.

Interestingly, this hypothesis means it’s Bill Nye [the science guy]’s status as a science communicator, not his status as a scientist, that so scares the denialist community. This makes sense: almost all scientists in relevant fields support evolution without hesitation and have done so for a long time, but this means very little to the denialists: they are far more concerned with convincing the public than convincing the scientists. It’s the science communicators who are in direct competition with them for the trust of the public.

In some ways, science communication is a science unto itself (or maybe an art?) but communicating science is certainly not the same thing as teaching it. Successfully communicating science…. hmm… actually, there’s too much down that damn rabbit hole to go into in the last few paragraphs of this post, so I’ll leave Communicating Science as a topic for a later blog post. Suffice it to say, I think that at the point our society is at, science communication is almost as important as science itself.

Certainly science communication makes me hope that my work on Species will create something more lasting than an interesting game. Plus, if I can piss off the denialist community by even a fraction of the amount Bill Nye has done with his video, I’ll be laughing.


“Serious Question: in a fight between Bill Nye and Adam Savage, who would win?”


Dammit, now I’m wondering just how much energy really is contained in creationists. Let’s find out:

(We’ll confine ourself to American creationists since the statistics are better and, as Bill Nye [the science guy] says, modern creationism is a primarily an American phenomena)

Average Human Weight (male, US) = 88.6 kg
Average Human Weight (female, US) = 77.2 kg
Average Human Weight (US) = (88.6 + 77.2) / 2 = 82.9 kg

US population = 314,289,000 people (2012)
Creationist Percent of the US population = 43% (2007)
Number of US Creationists = (314,289,000 * 0.43) = 135,144,000 people

Mass of US Creationists = 135,144,000 * 82.9 = 11,203,440,000 kg

c = 299,792,458 m / s

E = mc^2 = (11 203 440 000) * (299 792 458) ^ 2
= 1.00e+27 joules
= 239 000 teratons

For comparison, the Chixlub impact that wiped out the dinosaurs has been estimated at a mere 100 teratons (a teraton is one million megatons). So for the sake of a comprehensible mental image, imagine more than 2000 “world killer” meteorites hitting America at the same time. (And in case you were wondering, this math puts the energy yield of a single person at 1780 megatons: our largest nuclear weapons (the full-yield tsar bomba) don’t even come close at 150 megatons).

Clearly there is only one sensible conclusion to draw from this: creationists are the power-source of the future. Somebody get those buggers running on treadmills!

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Genetic Programming and Limb Physics

Note: I realise my blog update schedule hasn’t exactly been regular recently. Truth is, I’ve been at a bit of a loss for things to write about. I could use some ideas. (The fact that I’ve been posting loads of potential blog material over on the forums instead of here probably doesn’t help).

I’ll try to get back to a every-Tuesday posting schedule in coming weeks, assuming I can think of something worthwhile to write about. In the meantime, here’s some disjointed thoughts.

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Species is a Genetic Algorithm, but it is not Genetic Programming.

Genetic Algorithms use mutation and selection to find the optimal solution to a problem. The problem to which Species looks for a solution is simply “survival”, in the context of the games environment, which adds some complexity and depth to the “problem” side of things, but the “solution” isn’t actually hugely complicated.

Creature Genetics in Species are simply a bunch of one dimensional numbers. There are exceptions, but most of the genetic values in Species can be represented as a simple slider. So the evolution in the game is simply pushing these sliders up and down on their axes. The interactions and dynamics between the ecosytem and the statistics add quite a bit of depth but ultimately it’s not a particularly deep solution.

The concepts of genetic programming are quite a bit deeper. Genetic Programs use a noded ‘tree’ structure: rather than pushing numbers up and down, mutations in a genetic program add and move branches of the tree around. These branches might refer to packets of code, if()then conditionals, or loops. Or, if we take the analogy a bit more literally, they might refer to branches.

This is actually closer to the way real-life evolution works, and I would quite like to implement some of these concepts into Species. GP concepts are much, much better at producing unexpectedly novel structures and behaviors.

Unfortionately, GP structures don’t evolve very fast, and Species is about *seeing* evolution in action. That video above encompasses 7 hours of evolution. This was exactly the problem I had with the original behavioral system, which used some similar idea’s: it was too complex and didn’t evolve fast enough to be relevant to the simulation. When I replaced it with the simpler aggression and social sliders, it became much more responsive to selection pressures.

But like I said, though I don’t have GP, I want it. I want it a lot.

* * * * * * * * * *

I am jealous right now, as I often am when looking at other evolution sims.

I cannot *begin* to describe how much I would *love* to build something like this into Species.

Unfortionately the only way to achieve that is to work out a way to fake it: physics like this is deadly to the framerate when you’re simulating more than one creature. Simulating 1500 is well and truly too much.

So… faking limb physics. My initial thoughts are that there are two ways to do this: top-down, or bottom-up.

The former involves Inverse Kinematics. The genes give us an indeterminate limb-shape, and at birth an IK algorithm takes that limb shape and makes it walk as best it can, similar to the way creatures in Spore could walk no matter the shape of the legs. We then reverse-engineer stamina and speed stats from the step motion.

The disadvantage to this is that even though the legs might look different, they will all be animated the same way. There won’t be any novelty to the motion. On the bright side, that motion will probably be (relatively) crisp and clean: the feet will reach the ground and will provide a good appearance of ‘pushing’ walking creatures along.

The second method is bottom-up: we give every joint in a creatures leg a ‘motor’ to run it, a few paramters to determine step size and speed, and we try to somehow analyse the result to give us a constant speed, or even better, a variable one. This is a painfully difficult method: it will cost a lot in terms of performance, and the physics probably won’t look great, but if it works it could have a lot of potential. The trick is in working out exactly how to *make* it work.

One possiblity is that ‘step size’ could be limited to fractions of a particular value. So step sizes could be 1.0, 0.5, 0.25, 0.2, 0.1… but not 0.8 or 0.3 or 0.15.

This would make the limb-movement cyclical, and we could simulate a single cycle of motion at birth to determine how fast the creature can move. This is an expensive operation, however, and might result in noticable lag-spikes during births if poorly implemented. It also has a limitation: if the creature moves forward in jerks and bounds, a constant movement speed would not register that and the creature would look like it was gliding (although there might be ways around that, maybe, I hope).

Don’t get your hopes up just yet, though. This is all very much long-term stuff, which I probably shouldn’t even be discussing publically, but hey: I had to post something. And this is the sort of stuff I consider for Species. 🙂



Defining Species

One thing about Species that I keep stressing, but which is easy to forget even for me, is that the simulation is random. It’s easy to say that a species “decides” to splinter from the main population and speciate, or to say that they’re “trying” to develop eyes and legs. But all of that is pure personification on our part: it’s like saying the ocean “decides” to have tides, or the clouds are “trying” to rain.

The ‘species’ category is a perfect example of this. I was showing a friend the game and caught myself saying that “once it comes back down from the population explosion, the simulation will make them speciate”. But that’s not how it works at all: the simulation doesn’t make them do anything. They don’t have to speciate any more than a million proverbial monkeys bashing on typewriters have to produce the Twilight series. The simulation simply detects speciation/vampire-romance after it occurs.

I could have adopted the top down approach, and made speciation something that the game makes happen after a certain amount of time or in response to certain events. That would probably have been much lighter on performance, and easier to code to boot.

But it would also have been cheating. Real life approaches things from the bottom up.*

So the speciation routine has no influence on the simulation. It’s completely passive, an exercise in analysis and display: computer-generated taxonomy. The creatures don’t know or care what species the game thinks they belong to, and the simulation would play out exactly the same with or without speciation detection. Whether or not creatures can mate is determined on an individual basis, not based on species.

This has allowed for some fascinating and unexpected effects. Quite often, a ‘speciation’ of a single creature will happen, appearing as a pixel-wide line on the population history. This is the result of a creature being born sterile (ie. mutated heavily enough that it is unable to mate with anyone else in the population). Since the creatures can reproduce without mating this creature can still have descendants, and may well become a stable species in it’s own right.

(Worth noting: a creature cannot be born into a new species, because a speciation test isn’t done for births: a newborn is simply given it’s parents species. If it is born sterile, it will speciate when the parent dies and breaks it’s link to the main population)

This system also makes for an interesting design challenge. See, two things that would make the simulation more interesting are an increased mating frequency (increasing the gene sharing and making things like sexual selection more apparent) and more speciation (making lots of small species rather than one large one). But in the current system, these two features are diametrically opposed: expanding the genetic compatibility range and allowing the creatures a wider variety of mates means populations have to distinguish themselves more before the game will detect a speciation.

One solution to this, suggested here by Icefire, is a ‘soft’ definition of species, not reliant on breeding compatibility. My problem with this is that it makes the ‘species’ category less well defined: rather than being “a collection of creatures capable of interbreeding” it becomes “a collection of creatures with an arbitrary amount of genetic similarity”.

But after some thought I decided I’m okay with exposing it for a future version. I think the default should always be the “Hard” definition of species (the game is called Species, after all) but using the softer options will allow you to make interspecies breeding possible.


*footnote: this top-down bottom-up discrepancy is an interesting spanner in the works of the Intelligent Design crowd. Design is an inherently top-down process: a designer starts with a goal and works out the simplest, most efficient method to achieve it. So designed objects tend to be mathematical and precise: straight lines and square corners. Natural objects, on the other hand, take a bottom-up approach: this molecule on that molecule, this rock on that rock, this gene on that gene, all clumping together to make up an object.

A designed room can be represented abstractly as a set of numbers: width, height and breadth for a simple rectangular prism. 3 numbers. A natural cave, on the other hand, can never be represented in full detail, because you’ll never have enough numbers. The unecessary complexity is evidence that it’s natural, not that it’s designed.

Which only makes it more jarring when denialists argue that the incomprehensible complexity of life is evidence of design. It seems like quite the opposite, from my perspective at least.

“Twilight Jokes. Statistically inaccurate Twilight Jokes. Wow, I didn’t think we could sink any lower.

The chances of pure randomness producing a particular work of fiction the length of one of Stephanie Meyer’s novels are quite significant**, and more importantly, are completely incomparible to a force like evolution, which is cumulatively influenced by forces like survival, gene-sharing and reproduction.


115362 words in Twilight * (5.10 (average number of characters per word) + 1.5 (rough guess for spaces and punctuation)) = ~761,000 characters.
1 in 49 = Odds of random key on typewriter being correct.
Odds of producing novel of this length in a single trial: 1 in 49^761000

Size of the universe = 3.1e84 (cm^3) / 4.22e-99 (planck cube volume) = 7.3e+182
Age of the universe in Plank time: 3.3 x 10^60
If trials could be condensed to the size of a cube 1 planck length on the side, and run once every plank time frame, a computer the size of the current observable universe would have performed 2.4 x 10^243 trials.

2.4*10^243 < 49^761000.

Ergo, if you want monkeys typing vampire romance novels, you're better off going into neuroscience or biology than mathematics. They've got better odds in the long run."


Oh no!

I haven’t modelled paedomorphosis or peramorphosis at all!

Pharyngula: Brains and Beaks

Crap! I’ll have to completely start over from scratch!

Okay, I am being mildly facetious there, but I hadn’t even considered the depth of the developmental model before now. It’d be nice to introduce a life-cycle a bit more advanced than the current system, which is:

Born (parent: -birthCost) => Child (-growthCost, averaged over childhoodLength) => Adult (can reproduce)

I wonder how we can improve on it…

“Don’t worry, we installed an “anti-feature creep” system for exactly this sort of situation. It drops a swarm of carnivorous tadpoles from the roof above his chair every time something like this happens. I’ll just go activate it.”


“Ah, excellent, it seems to be working. Release date is still Sunday, by the way. Cheers.”

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Why aren’t carnivores evolving?

Here’s a new type of post: analysing the behavior of Species: trying to work out why things are happening the way they are, and using what we learn to improve the mechanics for the future.

Eventually, I’d like to integrate this sort of questioning into the game mechanics themselves: make science itself a game mechanic. As an example: say you want to know what a specific gene does. The game could require you to earn a certain amount of “data points”, or something equally abstract, and then spend them on that gene to discover it’s function. And that would make for a decent game mechanic, encouraging you to earn data points, which I assume you’d get by performing actions like creature sampling. But it wouldn’t be science, it’d be economics. And no offence to economists and EVE Online players, but unless your entire country is falling into disrepair because of too many short-term investments and cuts by the rich and powerful, economics is boring.

Alternatively, you could take a creatures genome, apply heavy mutation to that gene specifically (via a targetable radiation gun or something equally awesome), then clone a creature from that genome and see what’s changed. You could then go back and label the gene. Observation, hypothesis, experimentation and conclusion: that’s science, turned into a gameplay mechanic. And best of all, the reward is the logical result of the experiment: you can now target that feature specifically when you manipulate genetics.

Of course, the game can take care of some of the slower bits: for instance, an ‘autocompare’ between parent and child, which detects and names the heavily mutated gene for you, would keep the game moving better than if the player had to visually inspect for differences, and then go back and type in the function of the mutated gene themselves. Afterall, I’m not interested in data entry, I’m interested in science. (On the other hand, if naming gene functions is your thing, this would tie in well with the ‘naturalist mode’ idea that Reprieve suggested)

Anyway, I’ve managed to go off track before I even got on the track in the first place. I don’t even think I ever even [i]saw[/i] the track: I’ve been doing donuts in the carpark this whole time. Shorter me: I’ll be looking for any opportunity I can to integrate science and gameplay. In the meantime, I can still do science on the game out here in meta-space.

And what I want to know today is: why aren’t carnivores evolving?

Play the game for a bit and the best you’ll probably get are omnivores, despite all the giant piles of delicious meat lying around. Something’s going on: hunting and scavenging should be viable strategies, so why don’t carnivores survive?

Part of this is simply the power of stupid. Creatures are often too dumb to seek out plants, let alone other creatures, let along dead other creatures. Rest assured I’m working on this for 0.4.1, and future versions will have significant AI improvements on top of it.

But it’s not just that. You may have noticed that probably the most viable strategy among the creatures is to find a large tree and just sit there eating it, staying at max energy and pumping out 10 or more babbies until it’s gone, like the Quiverful movement’s vision of the ideal woman.

So why doesn’t this work for carnivores?

Is it just simple math? I’ve been meaning to check the math for this post, but haven’t gotten around to it (and I don’t have the game in front of me right now durn it), but I’m pretty sure it isn’t: meat energy is highly dependant on the life of the dead creature, but everything they eat during their life is converted to meat, so there should be loads of it in each meat pile.

But there’s another factor. You see, creatures have an ‘eat rate’ value, which differs between vegetation and meat. The malleable, delicious, high-protein meat can be consumed much more rapidly than the tough, horrible, inefficient plants.

Seriously. We really appreciate it.

In theory, this serves as a reward: unlike grazing, creatures can get a lot of energy in a short amount of time from meat. In practice, it became the opposite: the above strategy, where creatures maintain their energy at max by eating from one source until it’s completely consumed, works for only as long as the source lasts. And meat doesn’t last much time at all.

This is an interesting phenomenamnicon in it’s own right: the ecosystem actually encourages slow-eating creatures, which is the opposite of my expectations. But it makes the game less interesting and actually discourages evolution, so I believe a few changes are in order.

There are two approaches I could take to this:

– The balancing approach. Consuming meat faster is preventing carnivores from developing, so I’ll make them consume meat slower. I’m not going to take this approach, partly because it’s illogical, but mainly because it utterly and unforgivably violates my primary design goal. I’m developing the environment, not the evolution: I shouldn’t be ‘balancing’ selection pressures to make the things that I find interesting develop. That’s not what the game is about! Aargh!

– The expanding approach. It’s not consuming meat faster that’s preventing carnivores from developing: it’s that I’ve failed to model the animals eating behavior correctly. It’s logically impossible for them to continue to eat when their stomach’s completely full, so why are they doing so? I need to fix that fundamental bug, rather than working within it to achieve outcomes I percieve as desirous.

Of course, I probably won’t be able to fix it immediately. Making them make a new decision when full is a relatively simple thing to implement, but it will lead to a whole bunch of new bugs to test for, and will have significant implications for their survival (making it much harder on the early, blind creatures, and much easier on the sighted random creatures). So I’ll probably hold off implementing it until 0.5.0, which will also implement grazing, a feeding strategy that doesn’t depend on sight and so makes it easier on the starting creatures.

(EDIT) Actually, you know what guys? Screw everything I just said, I’m implementing it anyway. I might as well: it’s not like I’m not fixing AI bugs already, and with those fixes I’ve already completely screwed over the game balance.

(EDIT Mk2) What the flip. The blind starting creatures are surviving better now? How are they… I don’t even… what is this? What the hell even is this? YOUR GOD DEMANDS TO KNOW.

(EDIT Mk3) Okay, it looks like this might be one of those hilariously unintuitive results the Anthropomorphic Personification Of Evolution is so fond of. I could explain what I think is causing it, but that would deprive you guys of the challenge of working it out yourself. So come on: tell me in the comments why they’re reproducing better now that they leave tree’s alone when they’re full! I’ll post what I think is the answer a few days from now.


“Phenomenon”: singular. “Phenomena”: plural. And the “Phenomenamnicon” is a book used to summon a particularly vague eldritch abomination. Geez, it’s not that hard to remember!

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Evolving Reproduction

Sorry this post is a day late. Administrative stuff has been occupying a lot of my spare time. Hopefully I’ll have a few surprises for you guys in time for the release… [ominous smile]

It’s been a while since I did an evolution/misinformation post. Better get onto that…

This claim probably qualifies as picking the low hanging fruit, but I’ve heard it enough times recently to finally lose my cool and deal with it. Those who use it prominently, evangelists like Ray Comfort and Eric Hovind, are surprisingly popular despite being some of the least intimidating intellectuals amongst the anti-evolutionist movement, so I feel the need express my awareness that this is kind of like picking on the special needs kid at school. I’ll will make an attempt to increase the local level of intellectualism somewhat by dealing with the fundamental disbelief that motivates this claim, but quite frankly, it seems likely I’ll descend into the incoherent noises of someone suffering first degree WTF.

The claim, to quote the aforementioned Mr Comfort, goes something like this:

“For example, evolution has no explanation as to why and how around 1.4 million species of animals evolved as male and female. No one even goes near explaining how and why each species managed to reproduce (during the millions of years the female was supposedly evolving to maturity) without the right reproductive machinery.” – Ray Comfort

The ignorance required to even make this claim is breathtaking. I get phantom keyboard pains in my forehead just thinking about it. Where to even start?

I suppose the first point to make here is fairly blatantly obvious to anyone who didn’t fall onto their head from the top of a ten story building: the theory predicts that sexual selection evolved once in the common ancestor of those “1.4 million species of animals”. I don’t know how Ray Comfort got to the end of the sentence without realising that this is obviously what the theory must predict, but he has somehow managed that weirdly impressive feat many times since: for several years he frequently made this bizarre argument, hundreds of times over. As far as I know Comfort himself finally seems to have stopped using the argument, but his followers most certainly have not.

The claim, despite being the equivalent of a lobotomised guppy in a swimming pool full of sharks, does have a more interesting basis: general disbelief in the evolution of sexual reproduction. Explaining the origins of dedicated sexual reproduction is a tricky one with few concrete answers, so seeing creationists asking gotcha questions about it online is not uncommon.

The first point is that, as is often the case, we can see a continuum of creatures in the ecosystem already. Plenty of asexual and hermaphroditic organisms exist, and there are a variety of creatures that fall somewhere in between. Even amongst our own species gender is hardly a binary male/female trait, and the animal kingdom makes the even the most varied among us look positively mundane. It’s not that hard to draw a line from the asexual to the sexual organisms once you gather up enough dots.

For sexual reproduction to evolve, it needs two things: a viable evolutionary pathway via multiple, progressive mutations (similar to the metaphorical line I wrote about above), and a benefit to following this pathway.

The benefit to sexual reproduction isn’t immediately apparent. Sexual creatures as individuals don’t survive any better than their asexual cousins: indeed, the necessity of finding a mate is quite a harsh impact on an individual’s ability to reproduce. But evolution isn’t about individuals: it’s about populations, and genes. A lot of people think of evolution in simple ‘faster leopard catches more food, faster leopard survives’ terms, when it often doesn’t work like that.

The benefit to sexual reproduction (well, okay, one of several) isn’t that the creature that mates survives, it’s that the population of creatures that mate can take advantage of beneficial mutations more efficiently than the populations that don’t. Amongst asexual creatures, every creature is in direct competition. In order for it’s genes to survive in the long term, it isn’t enough for creature A to survive and reproduce: creature A’s descendants have to survive and reproduce and continue to survive and reproduce, out-competing and avoiding being out-competed by the descendants of creatures B and C.

Assuming creature A’s lineage out-competes lineage B and C, any beneficial mutations amongst B and C will be lost.

Sexual reproduction introduces an entirely new dynamic: co-operation, rather than competition. Creature A’s lineage doesn’t have to out-compete B and C’s: instead they interbreed, merging their three lineages into one. This means that the beneficial mutations of all three creatures can make it into the descendant population. This co-operation is a surprisingly powerful benefit: so powerful that it prompted the development of a requirement to breed prior to reproducing.

The evolutionary pressure in favour of sexual selection, then, is that it increases the efficiency of evolution itself. Populations that evolve faster and more efficiently will, over time, be able to out-compete slower populations.

This is a large advantage to macroscopic creatures, for which the cost of reproduction is high. Microscopic creatures like bacteria and viruses see less benefit from this: they can easily compensate for the lack of efficiency by cranking out ridiculous numbers of offspring at a rapid pace.

All of this is fairly theoretical and abstract, but one of the things I’ve been very happy to see is that it is replicated in at least some form in Species. Individual species usually do become more amorous over time, without me ever having had to implement any direct advantage to mating.

My hope is that tools in future versions of the game will help us dig down even further, to establish exactly why this is the case, by (for example) comparing the most successful half of the population to the less successful half, and highlighting the largest changes.

Another hope for future versions of the game is to improve the evolution of sex. Currently, all creatures can reproduce sexually, and their ‘amorousness’ behavioural modifier increases the chance they’ll mate upon encountering another of their kind. When they mate, both creatures take a copy of the others genetic code. Whenever they subsequently reproduce, they blend their own genetic code randomly with that of their mate to produce the offspring.

So they can and do evolve from asexual (never mates) to sexual (mates whenever given the chance), but it’s a very simple spectrum, and even the most sexual creatures are still capable of reproducing without mating. Adding additional complexity in this system, like possible birthing restrictions and maybe even gender differentiation, would be worthwhile.

As a friend said recently, the feature creep potential for this game is practically infinite. Good thing I’m not trying to implement everything before release!


Hmm… I had actually meant to do a thought experiment fr this post: try to work out the most likely evolutionary pathway from basic splitting to gender differentiation. Oh well, some other time I guess.

Here’s something we found while Googling around for the relevant Ray Comfort quote”: “Darwin theorized that mankind (both male and female) evolved alongside each other over millions of years, both reproducing after their own kind before the ability to physically have sex evolved. They did this through “asexuality” (“without sexual desire or activity or lacking any apparent sex or sex organs”). Each of them split in half (“Asexual organisms reproduce by fission (splitting in half).” – Ray Comfort.

The Banana Man, ladies and gentlemen. Accept no subtitute.

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Not everything in Species has gone the way of the behavioural system, getting simpler and simpler over time. Some things, like lifespan, have actually been becoming more complex over time, slowly integrating themselves with more and more systems in the game. (Don’t worry, I’m like 80% certain none of them are about to become Skynet)

As already mentioned in previous posts, lifespan initially wasn’t included. Once reproduction was put in place, however, we needed to ensure there existed ways to die beyond “brutally murdered by the developer”, which up until then was the only cause of death.

This was something I hadn’t designed from the start: how lifespan should be handled simply hadn’t occurred to me. So to start with, I did the simplest thing and just killed the creatures the moment they hit a certain age. From memory it was 2 minutes simulation time.

This was a pretty blatant instance of placeholder abuse. The lifespan was artificial and arbitrary, but I told myself it was just a placeholder so it didn’t matter and moved on with other things.

As it turned out this self-serving assumption was both true and false. True, it didn’t matter at the time I implemented it: at that point energy leaks and AI bugs made balancing the game a futile endeavour. But it did come to matter later, because as it turns out, 2 minutes isn’t enough time to find food and reproduce. Who’d a thought?

The next iteration (after upping the lifespan variable to compensate several times) was to turn lifespan into an inheritable value.

This turned out to be an interesting solution. Creatures with a longer lifespan would spend longer in childhood, unable to breed. This meant that creatures would have to find the right balance.

Unfortunately, it was impossible to guess a creature’s lifespan from visual cues. It was the same problem I was having with the behavioural system: you couldn’t see lifespan evolution happening, at least not directly. I needed to tie lifespan to something physical.

The third step was to tie lifespan to size. Larger creatures live longer than smaller creatures, right?

This was a lot better, and it made it possible to see the effects lifespan was having on natural selection. It still felt a bit arbitrary (it was possible to put a countdown-to-death timer on top of every creature based purely on their size), but it wasn’t a bad system.

But at this point I realised something else that was bothering me about all these systems: they were instantaneous. Age and lifespan had absolutely no effect on a creature until suddenly and without warning they exploded into mounds of delicious meat. This doesn’t normally happen in real life (well, except that one time I mixed up the nitroglycerine and the cat food, but that was totally* an accident).

The energy system at the time also meant that creatures dying of old age had far more meat on their bones than creatures killed by attacks or starvation, because their energy and health bars were often still full when they died, so they got converted to meat. This side-effect was unexpected, and unless you understood the system behind it, didn’t make much sense.

The fourth implementation (or possibly the 3.5th) was an adaptation of the previous version, where rather than just getting insta-gibbed, creatures past their use-by date would gain a new energy cost, similar to the cost of growing out of childhood. This “dying” cost would deplete their energy and health bars, resulting in a much more natural-seeming death.

But I still wasn’t happy with it. It was theoretically possible for a creature to eat enough to offset the dying cost and live forever, and increasing the age cost enough to counter that possibility simply made it look like I was insta-killing them again. It wasn’t that big of a problem, but I still wasn’t happy with the system. It just didn’t feel right.

And so I finally got around to giving the problem the attention it deserved in the first place. How does lifespan work in real life? (Morbid discussions on the nature of mortality! That’s what this blog needs more of!)

In real life, the damage from age is gradual and increases over time. We don’t suddenly hit a certain age and keel over, we just slowly take more and more damage until our body can no longer keep running. We can offset this with a healthy diet, exercise, and homeopathic remedies… pfff no I’m kidding. Stick with the healthy diet and exercise, at least they do stuff. Anyway, we can offset the damage significantly, but we can’t offset it forever, because it accelerates as we age. It was relatively easy for humanity to get our average lifespan up to 80, but now we’re struggling for every extra year, even with the incredible advances in medical technology we’re seeing in recent times.

So how does this translate to Species? Fifth implementation: aging doesn’t suddenly kick in at the end of the creatures lifespan, instead starting slowly and accelerating over time. Young creatures just out of childhood spend very little energy on keeping their body running, while older creatures spend ever-increasing amounts. This ensures that no matter how quickly a creature can gather energy, it’ll never be able to stave off death indefinitely.

Of course, I still want longer and shorter lived creatures correlated with size, without just handing an indisputable advantage to the largest creatures on the map. A bit of further thought/research on the subject revealed something interesting: smaller, shorter lived creatures in real life tend not to show signs of aging until the very end, while larger creatures die more slowly. This gave me an idea: a variable energy loss curve.

As you can see, small creatures (x3) have the advantage early in their life: more energy to spend on moving, eating and reproduction, but then their energy loss accelerates sharply towards the end of their life. Large creatures (c*x) lose the early advantage in favour of a much higher staying power. In-between creatures lerp (linearly interpolate) between these two graphs.

An interesting point about all this extra complexity in lifespan determination: it doesn’t obscure the in-game evolution the way the complexity in the behavioural system did. The ‘mutable lifespan’ I had way back in step 2 was a lot simpler than this, but also a lot harder to spot in action. I assume that’s because this system matches what we intuitively know about the world: larger creatures live longer, smaller creatures are more energetic (ask any dog owner). The complexity here just gives the system more nuance, making it feel more natural.

So I guess the take-home message is: complexity is not the enemy of intuition. A familiar but complex system is preferable to a simple but alien system.

I’m totally deep!

*footnote: For the record, whenever I use the word “totally” in this context, I am, like, totally being ironic. I don’t generally speak like a high schooler from the 90’s. Dude.

“The neighbour’s cat was probably lucky it was only nitroglycerine. He stores mutagenic nanobacteria on the next shelf down.”

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Oh nooooo… we’ve just run into a huge problem, guys.

I’ve been reading some recent groundbreaking research from a few vulnerable institutions, and have realised that there is a fourth mechanism in play in biological evolution that I’ve failed to account for. This is going to throw a huge spanner in the works: this mechanism is so fundamental to biology that I’ll have to strip the game down to basics to implement it.

It’s hard to explain the mechanism I’m referring to in laymen’s terms, but I’ll try. It’s a homogenising force, sort of like a “genetic memory” in the average population that, over the course of the species development, selects against extensive mutation. A natural biological pullback, if you will, which prevents an overabundance of cancerous and negative mutations killing off the entire population.

It’s not necessarily related to dominance in genes: even though heterozygotes seem to experience amplified effects, the phenomenon has been observed in recessive epistasis locii as well, so even though the creatures in Species all exhibit signs of codominance, it is something that has to be accounted for, because otherwise we would see exponential hypermutation in the genotype compared to the relatively limited affinity maturation we actually see.

I’m sad to say this is a major setback, but mistargeted somatic hypermutation has a powerful complementarity determining effect on diploid populations, and it would be extremely negligent of me to not implement this Tautomerism (probably via binomial coefficients derived from Pascal’s triangle). At least I can replicate slipped-strand mispairing with pyrimidine dimer fairly easily without sacrificing the spheniscidae and loss of medusozoa of the relatively high frequency drosophila melanogaster. Like a Musa acuminata, you see?

Unfortunately, this will likely set the release date back a few months, but honestly I don’t have a choice here. Until I implement the Kind Barrier, the game just isn’t a realistic simulation of real life biology.



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