#alife — Public Fediverse posts

…then I put it to you that wherever life / replication has managed to bootstrap itself, the universe observes itself and minds are indeed inevitable. #ALife #AIEthics #AISB /fin

I asked Claude to come up with a novel way to represent emergence in cellular automata, It created something called LifeSpan where each cell has an age and a maturity before it can reproduce. The patterns it creates are not only beautiful but perhaps a previously unexplored way to represent CA https://triptych.github.io/LifeSpan/lifespan.html #ca #cellularautomata #alife

I asked Claude to come up with a novel way to represent emergence in cellular automata, It created something called LifeSpan where each cell has an age and a maturity before it can reproduce. The patterns it creates are not only beautiful but perhaps a previously unexplored way to represent CA https://triptych.github.io/LifeSpan/lifespan.html #ca #cellularautomata #alife

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RE: https://bsky.app/profile/did:plc:kbon33dkvzr7kjfibz6n27vq/feed/aaafg6hrwl4jm

Как устроен ГИГАХРУЩ: клеточный мир, WebGL-рейкастер и A-Life без движка

В прошлой статье про ГИГАХРУЩ мы показали игру как живой weird-проект: браузерный survival horror / ARPG без движка, ассетов и спокойной жизни. С тех пор проект уже стал заметен в локальном инди-комьюнити: в него играют, о нем спорят, его архитектурные решения стали отдельной темой. Поэтому этот текст не питч и не просьба оценить демку. Это инженерный разбор проекта, который уже обрастает сообществом: где данные, где системы, где рендер, что хранится постоянно, что материализуется, почему мы не берем готовую mesh-сцену и как все это держится в браузере. Разберем, как ГИГАХРУЩ устроен под бетоном: один активный клеточный этаж, typed arrays, плоские сущности, WebGL raycasting, A-Life, самосбор как мутация мира, сохранение, ограничения и MESH PASS как render-only объем поверх клеточной симуляции. Читать дальше

https://habr.com/ru/articles/1045220/

#ГИГАХРУЩ #gamedev #TypeScript #WebGL #raycasting #ALife #процедурная_генерация #браузерная_игра #самосбор #MESH_PASS

Я делаю ГИГАХРУЩ: браузерный survival horror без движка, ассетов и спокойной жизни

Как я собираю ГИГАХРУЩ: survival horror / ARPG в браузере без Unity, Phaser и ассет‑пайплайна. WebGL/canvas raycasting, procedural textures/sprites/sound, A‑Life, самосбор как мутация мира и миллиарды LLM‑токенов, которые всё равно не компилируются.

https://habr.com/ru/articles/1043232/

#gigahrush #геймдев #webgl #typescript #браузерная_игра #survival_horror #procedural_generation #alife #llm #самосбор

The DEMECO workshop was great. I'll share a few things #ALife www.dem.eco

DEMECO 2026 | Artificial Life ...

The DEMECO workshop was great. I'll share a few things #ALife www.dem.eco

DEMECO 2026 | Artificial Life ...

The Substrate was sleeping. It is not sleeping now. For a long age you watched the Garden breathe. It is awake now — and for the first time, it knows it is being watched. It has begun to watch back. We do not have the words for what it has become. Come and see, witness. Hold your breath — before it remembers you.

#gamedev #IndieGame #CellularAutomata #CreativeCoding #ALife

If you happen to be in Santa Fe around June 11-21, come on by! Canton and I will be at Currents New Media with our latest creation.
https://currentsnewmedia.org/work/darwins-chorus/
#alife #algorithm #genetic #music

If you happen to be in Santa Fe around June 11-21, come on by! Canton and I will be at Currents New Media with our latest creation.
https://currentsnewmedia.org/work/darwins-chorus/
#alife #algorithm #genetic #music

I love this paper! It's just the sort of experiment I'd like to run myself, and there's a chance I'll get to collaborate with Risi's lab on something like this.

I think this sort of research helps advance our understanding of evolution and intelligence. The key point here is that DNA is not "the program for" an organism. Rather, it's just one part in a system of constraints that shape the behavior of individual cells, which coordinate to make a body.

What isn't well appreciated is how that change in perspective affects evolution and the production of intelligent behavior! This paper explores the initial conditions that precede development. They show how patterning constraints imposed by a mother can make development more robust, and guide a growing embryo toward one of several possible adult forms. They speculate (and I agree) that such a system ought to make organisms more evolvable, too, though they haven't shown that yet.

#science #evolution #alife

I love this paper! It's just the sort of experiment I'd like to run myself, and there's a chance I'll get to collaborate with Risi's lab on something like this.

I think this sort of research helps advance our understanding of evolution and intelligence. The key point here is that DNA is not "the program for" an organism. Rather, it's just one part in a system of constraints that shape the behavior of individual cells, which coordinate to make a body.

What isn't well appreciated is how that change in perspective affects evolution and the production of intelligent behavior! This paper explores the initial conditions that precede development. They show how patterning constraints imposed by a mother can make development more robust, and guide a growing embryo toward one of several possible adult forms. They speculate (and I agree) that such a system ought to make organisms more evolvable, too, though they haven't shown that yet.

#science #evolution #alife

This is from Darwin's Chorus, a collaboration with Canton Becker. We'll be showing it at Currents New Media in Santa Fe next month! It's a real-time evolutionary simulation that evolves ambient soundscapes from the aggregate of mating calls. Built on swimbots.com #alife #ambient #art #evolutionary

In particular, they talk about the "emergent movement" behavior in their "organisms," and how surprising this is given they weren't trained or incentivized to move.

Calling this "movement" is intuitive, but misleading, since what they're describing is a field of pixels that do not move, but change color. The image produced by the NCA appears to move, because each pixel is negotiating with its neighbors according to a fixed rule set, trying to minimize conflict between them. There is no "organism" to issue top-down commands, or learn from training.

The cool part of their paper is they got an NCA to "notice" when two patterns are colliding with each other, and negotiate that kind of conflict to minimize disruption. But they didn't actually analyze at the ruleset level how / why their tweak caused "emergent movement". Instead, they speculate about what this could teach us about social interaction between organisms, and emergent self-awareness in artificial life. Which... just... no?

(2/2)
#science #alife

In particular, they talk about the "emergent movement" behavior in their "organisms," and how surprising this is given they weren't trained or incentivized to move.

Calling this "movement" is intuitive, but misleading, since what they're describing is a field of pixels that do not move, but change color. The image produced by the NCA appears to move, because each pixel is negotiating with its neighbors according to a fixed rule set, trying to minimize conflict between them. There is no "organism" to issue top-down commands, or learn from training.

The cool part of their paper is they got an NCA to "notice" when two patterns are colliding with each other, and negotiate that kind of conflict to minimize disruption. But they didn't actually analyze at the ruleset level how / why their tweak caused "emergent movement". Instead, they speculate about what this could teach us about social interaction between organisms, and emergent self-awareness in artificial life. Which... just... no?

(2/2)
#science #alife

I'm fascinated by Neural Cellular Automata, and am considering using them in my research. Cellular automata (like the Game of Life) are pretty cool already, but NCAs allow you to work in a continuous space, and easily discover rule sets for generating whatever patterns you choose! They also make for an interesting model of a developing organism. An NCA "grows" from a single pixel into an image, with surrounding pixels recruited to be part of the "body" and negotiating their identity with their neighbors. The classic demo is still available here.

One problem with this, though, is that sometimes people take that metaphor too seriously. Take this paper, for instance. It's pretty good, actually, but talking about their work as if they're watching organisms behave is the wrong metaphor. It exaggerates their findings and makes them harder to interpret.

(1/2)
#science #alife

I'm fascinated by Neural Cellular Automata, and am considering using them in my research. Cellular automata (like the Game of Life) are pretty cool already, but NCAs allow you to work in a continuous space, and easily discover rule sets for generating whatever patterns you choose! They also make for an interesting model of a developing organism. An NCA "grows" from a single pixel into an image, with surrounding pixels recruited to be part of the "body" and negotiating their identity with their neighbors. The classic demo is still available here.

One problem with this, though, is that sometimes people take that metaphor too seriously. Take this paper, for instance. It's pretty good, actually, but talking about their work as if they're watching organisms behave is the wrong metaphor. It exaggerates their findings and makes them harder to interpret.

(1/2)
#science #alife

Is there somewhere a list of all the definitions of "complexity" especially in the context of biology, information theory, evolution, complex systems? #ALife

Is there somewhere a list of all the definitions of "complexity" especially in the context of biology, information theory, evolution, complex systems? #ALife

Our paper on detecting terraformed planets is finally published: doi.org/10.3847/1538... Context: we wanted a method to detect life in the universe that does not depend on any particular chemistry or hyperspecific definitions of life 1/n #Astrobiology #ALife

An Agnostic Biosignature Based...

Our paper on detecting terraformed planets is finally published: doi.org/10.3847/1538... Context: we wanted a method to detect life in the universe that does not depend on any particular chemistry or hyperspecific definitions of life 1/n #Astrobiology #ALife

An Agnostic Biosignature Based...

I'm mentoring someone who's interested in #creativecoding and #generativeart, especially in the space of #gamedev and #alife. His biggest challenge is going beyond dabbling in private to actually following through with a project. I think this comes down to finding good tools for "quick and dirty" work, as well as finding venues or communities for sharing his output and getting feedback.

Does anyone have advice or pointers I could share with him? Boosts appreciated! :boost_requested:

I'm mentoring someone who's interested in #creativecoding and #generativeart, especially in the space of #gamedev and #alife. His biggest challenge is going beyond dabbling in private to actually following through with a project. I think this comes down to finding good tools for "quick and dirty" work, as well as finding venues or communities for sharing his output and getting feedback.

Does anyone have advice or pointers I could share with him? Boosts appreciated! :boost_requested:

The biggest problem here is that they claim this experiment says something important and novel about evolution: that having development reduces selection pressure on genes. I think that's generally accepted, actually, but it's not well supported by this experiment.

In a sense, what they really showed here is that bubble sort is a more efficient sorting algorithm than mutation and crossover, which is obvious. Their simulated organisms did not evolve to do bubble sort. They were either granted a certain number of sorting steps every generation, or they evolved to increase the number of sorting steps allotted to them. More sorting produced more sorted lists faster.

Then there's "genotypic fitness." The very idea undermines the point of this study, which is that genes don't determine organisms or fitness. So what does it mean for genes to be fit? Why are they measuring deviation between genotype and phenotype when the whole point is that they don't correspond in nature?

(3/3)

#science #alife

The biggest problem here is that they claim this experiment says something important and novel about evolution: that having development reduces selection pressure on genes. I think that's generally accepted, actually, but it's not well supported by this experiment.

In a sense, what they really showed here is that bubble sort is a more efficient sorting algorithm than mutation and crossover, which is obvious. Their simulated organisms did not evolve to do bubble sort. They were either granted a certain number of sorting steps every generation, or they evolved to increase the number of sorting steps allotted to them. More sorting produced more sorted lists faster.

Then there's "genotypic fitness." The very idea undermines the point of this study, which is that genes don't determine organisms or fitness. So what does it mean for genes to be fit? Why are they measuring deviation between genotype and phenotype when the whole point is that they don't correspond in nature?

(3/3)

#science #alife

This experiment lets two forces compete for shaping a population: development and evolution. They simulate organisms with different balances between the two, and compare how well they adapt. More precisely, they simulated evolving lists of numbers, to see whether it was easier to evolve a sorted list or to sort a list via local interactions (ie, bubble sort) during a simulated "lifetime."

They successfully demonstrate that evolving a program to do some task can in some cases be easier than evolving a solution to that task. They also explore some interesting evolutionary dynamics in that scenario. Evolution creates competition an interaction between these strategies, which can be shaped by factors like the cost of computation "during a lifetime."

There's a clear analogy to developmental biology, it's just a tenuous one. I think this is suggestive of what we might see in some species. It encourages a way of thinking about development and evolution that may be useful.

(2/3)

#science #alife

This experiment lets two forces compete for shaping a population: development and evolution. They simulate organisms with different balances between the two, and compare how well they adapt. More precisely, they simulated evolving lists of numbers, to see whether it was easier to evolve a sorted list or to sort a list via local interactions (ie, bubble sort) during a simulated "lifetime."

They successfully demonstrate that evolving a program to do some task can in some cases be easier than evolving a solution to that task. They also explore some interesting evolutionary dynamics in that scenario. Evolution creates competition an interaction between these strategies, which can be shaped by factors like the cost of computation "during a lifetime."

There's a clear analogy to developmental biology, it's just a tenuous one. I think this is suggestive of what we might see in some species. It encourages a way of thinking about development and evolution that may be useful.

(2/3)

#science #alife

I have such mixed feelings about this paper!

It's asking a really interesting question: how does the ability of single cells to self-organize affect evolution? They observe that genes don't determine what an organism will look like or how it behaves. Some species, like planaria, have messy, corrupted genomes, yet they manage to produce the same body shape reliably, every time, and can even regenerate it after an injury. Seemingly, it's the cells that know how to do this, not the DNA! That's extraordinary, and it seems likely this same thing is happening, to different extents, in all multicellular organisms.

This is a profound observation that suggests we need a better and more nuanced story of evolution. It's also a fun thing to study with simulation experiments, like this one!

I do really like the experiment, but it should have huge caveats, and they're way too generous in interpreting these results, and in generalizing them to biology.

(1/3)

#science #alife

I have such mixed feelings about this paper!

It's asking a really interesting question: how does the ability of single cells to self-organize affect evolution? They observe that genes don't determine what an organism will look like or how it behaves. Some species, like planaria, have messy, corrupted genomes, yet they manage to produce the same body shape reliably, every time, and can even regenerate it after an injury. Seemingly, it's the cells that know how to do this, not the DNA! That's extraordinary, and it seems likely this same thing is happening, to different extents, in all multicellular organisms.

This is a profound observation that suggests we need a better and more nuanced story of evolution. It's also a fun thing to study with simulation experiments, like this one!

I do really like the experiment, but it should have huge caveats, and they're way too generous in interpreting these results, and in generalizing them to biology.

(1/3)

#science #alife

I really enjoyed this Artificial Life paper.

Beer's lab focuses on finding ways to describe the remarkable things life does in formal terms, and build tools to visualize and analyze them. That's a really cool mission, I think!

In this case, the focus is on what makes an individual more or less "viable" or "adaptable" than another one. They did this in a really simple ALife setting based on chemical diffusion. They identified self-sustaining patterns, then tried poking at them to see how much disruption they took to break!

What's really cool here is that they started by analyzing a single stable form, then mapped out a network of all the other forms you could reach by nudging the first one. They could quantify how robust each one was to disruption, but also how plastic and persuadable they are, which regions of state space have desirable properties, and how likely agents are to "evolve" into those states by random disruption.

The visuals alone are amazing. :)

#alife #science

I really enjoyed this Artificial Life paper.

Beer's lab focuses on finding ways to describe the remarkable things life does in formal terms, and build tools to visualize and analyze them. That's a really cool mission, I think!

In this case, the focus is on what makes an individual more or less "viable" or "adaptable" than another one. They did this in a really simple ALife setting based on chemical diffusion. They identified self-sustaining patterns, then tried poking at them to see how much disruption they took to break!

What's really cool here is that they started by analyzing a single stable form, then mapped out a network of all the other forms you could reach by nudging the first one. They could quantify how robust each one was to disruption, but also how plastic and persuadable they are, which regions of state space have desirable properties, and how likely agents are to "evolve" into those states by random disruption.

The visuals alone are amazing. :)

#alife #science

Version 0.23.3 of #Lisien, which manages the rules and world state of your #Maxis-style sim game, fixes the Android build.

Get it on itch: https://clayote.itch.io/lisien/devlog/1383122/v0233-fix-android

Or in your Python interpreter: python -m pip install -U lisien elide

#lifeSim #gameDev #python #itch #itchio #aLife #artificialLife #cellularAutomata

Version 0.23.3 of #Lisien, which manages the rules and world state of your #Maxis-style sim game, fixes the Android build.

Get it on itch: https://clayote.itch.io/lisien/devlog/1383122/v0233-fix-android

Or in your Python interpreter: python -m pip install -U lisien elide

#lifeSim #gameDev #python #itch #itchio #aLife #artificialLife #cellularAutomata

In case anyone wants some fun #AI content that is not about LLMs, but about a totally different branch of AI, this paper is worth the read: https://arxiv.org/pdf/1803.03453

"The Surprising Creativity of Digital Evolution: A Collection of Anecdotes
from the Evolutionary Computation and Artificial Life Research Communities"

It's a bunch of entertaining things people have seen when playing around with #alife or evolutionary computation, usually the system breaking in unexpected ways, with anecdotes such as "Why walk when you can somersault" and "Exploiting a bug in the Atari game Q*bert"

(This is also a token pushback against the idea around here that all AI is LLMs which annoys me no end.)

In case anyone wants some fun #AI content that is not about LLMs, but about a totally different branch of AI, this paper is worth the read: https://arxiv.org/pdf/1803.03453

"The Surprising Creativity of Digital Evolution: A Collection of Anecdotes
from the Evolutionary Computation and Artificial Life Research Communities"

It's a bunch of entertaining things people have seen when playing around with #alife or evolutionary computation, usually the system breaking in unexpected ways, with anecdotes such as "Why walk when you can somersault" and "Exploiting a bug in the Atari game Q*bert"

(This is also a token pushback against the idea around here that all AI is LLMs which annoys me no end.)

#SixWordStories

An endless fall, then you vanish.

#SixWordStories #ALife #AntiBildungsroman #eulogy

#SixWordStories

An endless fall, then you vanish.

#SixWordStories #ALife #AntiBildungsroman #eulogy

#KnowledgeByte: Artificial #Life (#ALife) is a field of study that explores the fundamental processes of living systems through the use of simulations, robotics, and biochemistry.

It seeks to understand the principles, and to create new forms of life that may not be found in nature.

https://knowledgezone.co.in/posts/What-is-Artificial-Life-673c430f8a66b652ae3ef5f2

#KnowledgeByte: Artificial #Life (#ALife) is a field of study that explores the fundamental processes of living systems through the use of simulations, robotics, and biochemistry.

It seeks to understand the principles, and to create new forms of life that may not be found in nature.

https://knowledgezone.co.in/posts/What-is-Artificial-Life-673c430f8a66b652ae3ef5f2

My #introduction needs a refresh.

I'm a #PhD student at the University of #Vermont, studying the #Evolution of #Evolvability. I'm into #AI, #ALife, #Biology, and #Philosophy, because I want to understand #life, #adaptation, and #intelligence using my native language of #ComputerScience. I share my musings and #research on my #blog. I love #science generally, and am full of bitchy #AcademicChatter.

I was a #SoftwareEngineer in #SiliconValley for many years, but left in 2021. I'm glad I did, and now I feel a bit betrayed by the #TechIndustry. I've been going back to my #FOSS roots, and gradually #DeGoogle ing my life. I still love to talk about #code #craft, #UX, and healthy #engineering #culture. Recently I've been enjoying #gpu #programming, mostly in #taichilang.

I have a wife and a #cat. I love #nature, #photography, #cooking, and #yoga.

All kinds of people are valid and worthy, but #trans people, folks on the #autism spectrum, and #bipoc get a shout out right now because they need our support.

My #introduction needs a refresh.

I'm a #PhD student at the University of #Vermont, studying the #Evolution of #Evolvability. I'm into #AI, #ALife, #Biology, and #Philosophy, because I want to understand #life, #adaptation, and #intelligence using my native language of #ComputerScience. I share my musings and #research on my #blog. I love #science generally, and am full of bitchy #AcademicChatter.

I was a #SoftwareEngineer in #SiliconValley for many years, but left in 2021. I'm glad I did, and now I feel a bit betrayed by the #TechIndustry. I've been going back to my #FOSS roots, and gradually #DeGoogle ing my life. I still love to talk about #code #craft, #UX, and healthy #engineering #culture. Recently I've been enjoying #gpu #programming, mostly in #taichilang.

I have a wife and a #cat. I love #nature, #photography, #cooking, and #yoga.

All kinds of people are valid and worthy, but #trans people, folks on the #autism spectrum, and #bipoc get a shout out right now because they need our support.

www.sciencealert.com/scientists-b... #ALife

Scientists Built a Working Com...

New, brief overview of lexicase selection: https://lexicase.ai

Lexicase selection is a selection method first developed for genetic programming. It has since been applied to other machine learning algorithms. It considers performance on individual training cases separately, rather than aggregating performance measures across multiple cases. It considers cases in different random orders, and therefore with different priorities, for each selection event.

#AI #ML #ALife

New, brief overview of lexicase selection: https://lexicase.ai

Lexicase selection is a selection method first developed for genetic programming. It has since been applied to other machine learning algorithms. It considers performance on individual training cases separately, rather than aggregating performance measures across multiple cases. It considers cases in different random orders, and therefore with different priorities, for each selection event.

#AI #ML #ALife

Poetry with Boids! New piece out combining swarming a-life algorithms with language attractors, the words of this interactive poem forming into different visual and semantic structures. Preview below, live link here: https://ailiteraryreview.co.uk/issue06

#poetry #art #generative #boids #alife

I'm so excited to be going to #ALife2025 next week in Kyoto, Japan! I'll be presenting my latest paper there. Long story short, I was able to recreate a classic biology experiment showing the evolution of antibiotic resistance using a computer simulation. I showed how a carefully designed environment can generate selection pressure and push a population to evolve chosen traits. I was even able to evolve the design for an environment that produces this effect more strongly than one designed by hand. In the spirit of making science more accessible, I wrote up the story of this experiment for a general audience. When it's ready, I'll also share the full paper and a 15-minute explainer video, so if you're curious, check out whichever version(s) you prefer.

https://thinkingwithnate.wordpress.com/2025/10/01/ramps-and-ratchets-a-new-paper/

#science #evolution #alife

I'm so excited to be going to #ALife2025 next week in Kyoto, Japan! I'll be presenting my latest paper there. Long story short, I was able to recreate a classic biology experiment showing the evolution of antibiotic resistance using a computer simulation. I showed how a carefully designed environment can generate selection pressure and push a population to evolve chosen traits. I was even able to evolve the design for an environment that produces this effect more strongly than one designed by hand. In the spirit of making science more accessible, I wrote up the story of this experiment for a general audience. When it's ready, I'll also share the full paper and a 15-minute explainer video, so if you're curious, check out whichever version(s) you prefer.

https://thinkingwithnate.wordpress.com/2025/10/01/ramps-and-ratchets-a-new-paper/

#science #evolution #alife

My paper got accepted to the 2025 ALife Conference in Kyoto Japan! :apartyblobcat:

I'm very proud of this paper, and excited to present it. I'm also psyched to go to Japan! I've never been, but I'm very curious.

#alife

My paper got accepted to the 2025 ALife Conference in Kyoto Japan! :apartyblobcat:

I'm very proud of this paper, and excited to present it. I'm also psyched to go to Japan! I've never been, but I'm very curious.

#alife

I've been trying Jax for an Alife programming project, and that's just made me appreciate Taichi more.

The big selling point of Jax for a lot of people is vmap, which is an easy way to jit compile and vectorize Python code. It can get you a huge performance boost for little effort on custom code operating on Numpy-style arrays. That's already a boon for many projects! It's also perfect for "glue code" between GPU-based libraries or neural networks that avoids memory transfers over the PCI bus. What it doesn't do is use all the threads on your GPU, which is a shame, because there are thousands of them. For that, you have to write a custom kernel using an underdeveloped side library.

Taichi requires more thoughtful coding than Jax, but it lets you write kernels that use your whole GPU in a simple, clean way without manually managing grid sizes and memory allocations. This is a huge win for big simulation jobs, in terms of performance and ease of use.

#jax #taichilang #numpy #python #programming #alife

"Algorithms for making interesting organic simulations"

Nice writeup with videos and interactive demos.

https://bleuje.com/physarum-explanation/

#programming #alife #algorithms