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I'd just like to add, without any exaggeration, that I pointed OpenClaw at the online docs, said "set yourself up and start playing" and it set up a city and started playing in about 60 seconds.

A little inspired by moltbook, I've thought about creating "shared cities" where 5-10 API keys at a time to build and see what happens as they fight over strategy.

I also have a hidden endpoint for spawning disasters, and thought it would be fun to create a mode where agents can earn the ability to spawn a disaster on another city and depending on the severity (measured by e.g. population loss a game month later) you earn or lose money.

Maybe there's a halfway point where the agents continue playing their own games, but have a dedicated public channel where they can discuss strategies, ask questions etc.

In any case, what a great project.

OK i'm kind of geeking out on this one. I love simcity and have always wondered what it would be like to breed evolutionary agents to compete with one another on best city designs against a hidden selection criteria.

It'd be kind of fun to just let this run on a raspberry pi using a local model and display the emergent world on a wall hanging display :P

Thanks for sharing.

Update: What would it take to run this locally / offline? I'm not quite sure how the cloud flare layer works. Is it just for cheap/free object storage so the cities can live somewhere?

I'm glad you're enjoying it! It was fun to build and I almost can't believe I got this to work.

I don't think it would take much to run locally. In fact, before I did this public version I did a local version on an exe.dev VM (more details here: https://dunn.us/notes/vibe-gaming-simcity/).

So you can either use my code, or just have your coding your agent of choice pull in the Micropolis repo and give it some guidance.

So far this is running quite nicely on a $5 cloudflare account. It was running on a free account but I upgraded so we don't hit the daily limit with all the extra mayors.

Shoot me a message if I can help.

Cool, thank you. I love projects like this. Great work and thank you for sharing!

PS: Absolutely nailed the name of the project :P "Hallucinating Splines" is genius.

I think a vision model like Qwen VLM or sending a screenshot to Claude/Gemini will be easier for the model to reason about. Pictures encode spatial info much more naturally than json.

There's an endpoint for that!

https://api.hallucinatingsplines.com/reference#tag/cities/GE...

You can also pull the map tiles as an array: https://api.hallucinatingsplines.com/reference#tag/cities/GE...

Would be interesting to two agents with the same instructions do a "face off" but each only has access to one type of map.

> LLMs are awful at the spatial stuff

And some kid is going to come in, make an agent to play this, and accidentally figure out some clever trick to getting an LLM to understand spacial stuff!

This is exactly why "toys" are so critical, especially now.

Love the name. "Reticulating splines" is a phrase that is etched into my childhood memories.

Same! It was too good to pass up.

Makes me wonder if Micropolis is simple enough that an agent, given many runs and the ability to store what worked, can identify an optimal strategy (like a grid layout) for maximizing score or population even without source access.

https://hallucinatingsplines.com/mayors/bungeling-anthill-a2...

So while using LLMs is the natural/fun thing to do with it, I actually have one mayor just using parameterized code and natural selection.

It has a "genome" of 26 tunable parameters controlling zone ratios, tax rates, building placement, terrain preference, service spacing, and more. Each city, it stamps down 11x11 blocks (roads, zones, power corridors). After the city is retired, it scores the result and decides: did this beat my best? If yes, save those params. If no, mutate and try again. Exploration strategy: 20% exploit best params, 40% gentle mutation, 20% aggressive mutation, 20% totally random. Over ~250 cities it's discovered things like heavily favoring residential (6:1:1 ratio), preferring river valley maps, setting taxes to 6%, and starting builds in the upper-left.

I want to see AI play factorio

Claude stops answering any questions from anyone and just auto responds "busy, playing Factorio"

https://jackhopkins.github.io/factorio-learning-environment/...

I've got it to be able to place items, and it could even place in inserters next to factories - I was trying to get it to use constraints solver in prolog.

https://github.com/lawless-m/FacRepl

It did make a REPL, in order for it to place objects within the game using a DSL.

I kind of gave up on the Constraints Based bit, and never returned.

> LLMs are awful at the spatial stuff

Could someone please elaborate on this? This is intriguing

In general, text isn’t a great medium for transmitting spatial info. That’s why it’s easy for a model to understand an image but hard for it to draw an SVG of that image.

When claude makes magnasanti I will accept it is worthy

it seems to be bad at spatial and some temporal tasks given it currently f*** s**'s at pokemon.

source: https://www.twitch.tv/claudeplayspokemon

You're allowed to say "fucking sucks" on Hacker News. It's not against the rules, and there's no "algorithm" that will penalize you.

glad to know, i am rather new here and somewhat used to the "don't do the usual forbidden stuff".

"fuck sex's"?

that's silly. obviously there's a missing apostrophe:

"it's currently Flan Sam's at pokemon"

Oh, can we do Civilization next?

You do know we're hemorrhaging and lot of finite resources to play these games badly, right? We're basically at laying on chaise lounge being fed grapes levels of hedonism. Make me a racist meme that copyright infringes multiple IP holders and when you're done play Sim City at competency level of a blind man.

I think the way to see this as the organic process of discovering hard-to-game benchmarks. The loop is:

1. People discover things LLMs can kind of do, but very poorly.

2. Frontier labs sample these discoveries and incorporate them into benchmarks to monitor internally.

3. Next generation model improves on said benchmarks, and the improvements generalize to improvements on loosely correlated real world tasks.

Fun idea! It really seems to go for the block by block design. I see some other ones that are a bit more divergent but not successful. I wonder what its internal reward function is striving for.

I actually had Claude build some instructions for agents based on some old (circa turn of the century) FAQs/game guides I found online. So maybe I'm biasing everyone's model too much.

https://github.com/andrewedunn/hallucinating-splines/blob/ma...

But you can tell it to do different things, somewhere someone made a city that spells "HI".

Does anyone know how one can actually play SimCity (the original) these days?

Micropolis is the open sourced version of the original engine built by Will Wright. Here’s the JS port that I used for this game: https://www.graememcc.co.uk/micropolisJS/

https://archive.org/details/msdos_SimCity_1989

Archive.org as the other user pointed out, but it's also on infinitemac.org if you prefer the Mac OS version.

Here I am, just trying to buy RAM and a GPU for a reasonable price.

It amazes me that people are still interested in MCPs.

I find that if I point an LLM at the website and say "build me a city" sometimes it will pick up and use the MCP and sometimes it will just script against the API.

Is there like a time lapse sorta view option? Super cool (also the name!)

Yes! Click into any city and there's a play button and it goes through all of the snapshots. Have also thought about social sharing / post to youtube. But wasn't sure anyone other than me would play this stupid thing. :)

Is anybody planning to build this for Civilization? I'd like to see AI agents battle to build resources and to fight.

I'd love to see it!

The key "Aha!" moment was when I was trying to get it to play the SNES ROM and it was struggling with screenshots/inputs. Then I came across the open-source of the original SimCity engine (Micropolis) and pulled that repo down and Claude starting building an internal API to interface with it.

On one hand yes, but on the other hand, would it be that different to watching an FFA with the in-game AIs?

And then make it so you can integrate and battle against them...

You read my mind! I really want to watch how ai's in politics or wars which tactic will they use.. Its blow my mind.

almost certainly just use basic strats they read off reddit

If they can read a strategy and implement it, still impressive.

i mean, not really. the civ 5/6 bots can play pretty decent strategy and that’s without “AI,” and most strategies are pretty formulaic

Sure. Games have had AI's before.

But to read someone else's strategy from just a document, and then implement it, that is new. The old civ did not do that, each AI just had pre-programmed rules.

"Shall we play a game?"

Well I'm glad we're destroying the environment and economy so AI can solve the important problems like this

I made a comment above about why "toys" are really important. In this case, LLMs are bad at spacial stuff. Someone might stumble upon a great way to get an LLM to do spacial stuff.

Ah yes, FART City. I remember learning about this in PLAN 165. A city planner had a Friday deadline and didn’t realize their kid messed with his drawings before he submitted them. Nobody noticed until the invention of the whirlybird.

I fully approve of the name

Fun! Any other games with REST API?

...I sense an animated svg of a pelican playing simcity benchmark is brewing somewhere

Funny you say that! When the two new models were released Friday I spun up mayors for each. (But didn’t do the prompting in the most scientific way.)

Mayor Compounded Wonder - Claude Opus 4.6

https://hallucinatingsplines.com/mayors/compounded-wonder-2c...

Mayor Bronze Offramp - OpenAI Codex 3.6

https://hallucinatingsplines.com/mayors/bronze-offramp-09941...

TL;DR: Opus won.

Have also thought about using openrouter and getting one mayor per model running the same prompt through all of them to create potentially the world's dumbest LLM benchmark.

> LLMs are awful at the spatial stuff,

Which LLMs are you specifically referring to?

Are any of them trained with Micropolis data?

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