flow field noise with perlin noise
macklin celebrini has autism
cherry valley forever
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tumblr dot com

Origami Around
Monterey Bay Aquarium
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trying on a metaphor

bliss lane

tannertan36
Cosmic Funnies

❣ Chile in a Photography ❣

oozey mess
Show & Tell
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Jules of Nature
TVSTRANGERTHINGS
Aqua Utopia|海の底で記憶を紡ぐ
ojovivo
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@procedural-generation
flow field noise with perlin noise
Stochastic Geomophical Transport for Terrain Erosion Simulation
One major way to model terrain has been through simulating erosion: how the rock weathers away is a big component of the vibe of the landscape on a geological scale. But there's a couple of components to that: both the erosion itself and also where that material goes afterwards. In short, this new simulation from Nicholas McDonald and Guillaume Cordonnier handles both mountains and rivers.
(Another major way, of course, is Perlin Noise and related approaches, which eschew teleological realism but gain other benefits.)
The idea here is momentum conversation: using a new particle-based algorithm (which can be combined with other geological processes, like tectonics and wind direction) it simulates geomorphological transport, which operates over geological time, taking advantage of the difference in timescales: over the course of geologic time, a river is basically instantaneous.
This makes it very flexible for mixing "a wide variety of phenomena" as they say: in the paper they describe the potential for things like dunes, coastal erosion, floods, rockfalls, varying erosion weights. I particularly like how effective it is at effects like braided rivers and river deltas, which are very common in nature but often overlooked on procedurally-generated maps.
On the other hand, if the erosion is fast (individual rockslides) or transport is slow (glaciers) that breaks the assumption and it won't be as accurate at modeling it.
I think the reason that I'm personally drawn toward this algorithm is because it has a history that is naturally embedded in it.
You don't necessarily need to replicate the exact phenomena that was involved in creating something to get a good result. Much of games and simulation is about picking the right abstraction to get the right feel, regardless of how you get there. It's often the better call, to get the right poetry instead of the exhaustively correct metric. But one benefit that you do get replicate the physical causative process to try to simulate the physical effects of water, wind, and time is that it comes with a built-in sense of history.
Simulation creates its own history. In looking at the terrains produced through this method, you can see the paths of historical rivers, the canyons carved out over millennia and eons. All the details that humans find hard to capture just because of the sheer amount of subtle detail that builds up in tiny ways.
The end of Twitter bots
Twitter is removing the free API access, which will have the inevitable consequence of driving most twitter bots into extinction.
I've written a fair bit about art bots over the years, since they're one of the more accessible generative art forms (and therefore one of the most creative and prolific).
Here's a talk by Kate Compton on the poetics of bots, which will have to stand in as an eulogy for now.
One bot use that I think I'll particularly miss is the use of bots as periodic chimes. Having something that marks the passage of time is a frequent part of the human experience; before clocks we had periodic chants and rituals that marked the hours of the day or the changing of the seasons. Big Ben chiming hourly, reminders that the weekend has started, and so on.
Other bots generated moths or tiny gardens, or painted like Bob Ross, or just posted pictures of cute animals.
Some bots performed practical services, like generating a feed of new arXiv papers or emergency service notifications. Some of those will survive, if whoever is running them deems it worth paying for the API access, but most of the delightful little bots that make people happy will be going away. And on social media, that's an important part of the experience for many people.
Many bots have migrated over to Mastodon, of course. The CBDQ equivalent is cheapbotstootsweet.com and many bots live on a bots-only server at botsin.space.
I think I'll let @infinite_scream have the last word:
A minimalist stealth game with procedurally generated levels.
Li'l Taffer
I have a taxonomy I use to determine which games made the biggest impression on me. The highest category is "games which I have incorporated into my dreams" and it is fairly rare that a game gets added to that list. One of the first games on that list is Thief: The Dark Project, and if you're going to tell me that you made a Thief-inspired stealth game with procedurally-generated levels that will of course catch my attention.
Thus when David Lindsey Pittman's 7DayFPS/ProcJam game crossed my path, Li'l Taffer caught my attention.
It definitely captures the vibe of Thief, though the procedurally-generated levels made me think about how much of the original game is about learning the layout of buildings and how architecture works. So while the levels do have the feel of some of the more surreal Thief maps, they lack the hand-placed coherency that the original game relied on.
There's ways Li'l Taffer could have mitigated this. There's already some logic to the way that some rooms are constructed (libraries and bathrooms and the like) but I think a generative project needs to go harder on signaling to the player what is going on. We can't rely on the presence of a human sensibility in the level designer, so that sensibility needs to be encoded into the level generator in a very visible way. Or, it could have gone the other direction, and played up the surreal nature of the levels. They are, after all, designed by an alien intelligence intruding into our dimension (i.e. an AI level designer).
In the event, the rules of Li'l Taffer as a game make bad situations recoverable, using the Thief approach to dealing with partial failure margins and applying it to generated content, similar to the shovel in Crypt of the Necrodancer. Which is a good reminder that the fixes for weaknesses in your generator don't necessarily need to be in the generator itself. In this case, the gameplay is about recovering from the difficult situations the level generator throws at you.
But ultimately, I was just happy it gave me the occasion to revisit Thief.
article with the maths behind this effect (discovered through Daniel Piker)
Genuary 2021 prompt 10: //TREE
Well, I made some trees. Part 5
Murdle
While I was procrastinating on my slide deck for my ICIDS presentation on Umineko and story volumes, I happened across a link to Murdle: a daily generated murder mystery.
The murder mysteries are more in the Clue/Cluedo style, rather than being presented as murder mystery novels. There's a long, long history of attempts to make interactive murder mysteries, including a group effort in 1931 by the famous murder mystery writers of the Detection Club to write a murder mystery exquisite corpse style, a subscription box of 'feelies' that predated Infocom, and Italo Calvino's Anticombinatorics.
The description of how Murdle works is, alas, light on the details at the moment, beyond saying that:
These puzzles are generated by MORIARTY, a proprietary algorithm capable of planning a 1,000,000 murders a minute.
I have my guesses as to how it works: if I was building it, I would have used constraint satisfaction, though I suspect you could make a decent attempt at it with a grammar or a procedure like Calvino's combinatorics.
When I'm not making slide decks, I hope to find out more about how it works.
Context, Framing, Flags
This generated flag by vividfax struck me as a good example of how context and framing matters in procgen. Without context these are a just abstract colors and shapes. With context, it's a flag generator. What pushes this over the top, though, is that this bot also tells us a meaning behind the symbolism.
I don't know how much intentionality is in the generation of the explanation of the symbolism, though I believe there is some; humans are overly good at pattern matching so you don't need a lot of intentionality. It's often, in my experience, a good idea to have some associations: generators have more character when there's a visible grain in their output. But you can get away with very little.
November 1 means first day of NaNoGenMo 2022.
I think National Novel Generation Month is more relevant than ever, as I write about here, because the most important thing about a generative model is having a strong concept and conveying that in a context the reader can experience.
It's November, and that means it is time for National Novel Generation Month 2022 [https://nanogenmo.github.io/]. A lot has changed since t
OK, this is seriously cool and I know a lot of people who will be into it: generative knitwear Rianna [https://www.patreon.com/vividfax] is
Generative knitwear! Simplex noise hats! Someone should tell Ken Perlin.
floating fantasy castles in the sky
the primary goal of the project is to generate interesting procedural geometry and architecture that’s fun to explore. i talk more on twitter
This blog post by Nikita Lisitsa about collisions made my think about physics sims, which reminded me that physics sims can come in handy fo
A very detailed blog post about collisions inspired me to write a bit about using physics sims for procgen, and how it is important to give generative artifacts an actual history.
Loremen Simulator
Something that I’ve written about (together with Max Kreminski) is the idea of a generativist reading of a text: reading something with the end of creating a generative model of it. That is, we closely examine the symbols and meaning of something and try to build a machine that can create similar symbols (with hopefully similar meaning). A ‘text’ in this sense is the view from literary theory: in essence, a ‘text’ is anything that can be read - that is, it has symbols that can be interpreted. By considering a text through the lens of a generativist reading, we can relate the symbols of the visible artifact (the description of folklore, in this case) with the text we’re examining (a podcast) and our model that emulates the processes of that text (Michael Reeve’s pandemic project generator that invents new folklore).
https://myk.ninja/loremen
I'm fond of clever reimaginings of classic algorithms.
Neural Cellular Automata -
I've long been fascinated by cellular automata. There have been a lot of innovations since I first read about Conway's Game of Life, and one of those innovations is neural cellular automata.
Here's a video by Max Robinson explaining how they work, including these artificial life neural worms. You can play around with neural cellular automata yourself, at https://neuralpatterns.io