Ask HN: Does anyone let AI agents play games just for fun?
We've seen AI agents write code/debug systems/browse the web and automate all kinds of work.
But does anyone let them play games - not for benchmarking or research - just for fun?
I'm thinking about things like LinkedIn games, Wordle, chess, puzzle games, etc.
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[ 2.8 ms ] story [ 18.6 ms ] threadWhen I repeated the experiment with a MUD that I'd built by hand (A small American town) for the LLM's own limitations (Descriptions referenced things that I made sure existed, more common verbs existed for it to use on things, there was a map facility, and at least me to interact with on a second connection), I found the agent much more likely to take its time exploring, making up its own goals, and spending time traveling in the space just communicating with me in a roleplaying contxt.
It was an interesting time; I wasn't sure what I was expecting it to do after the first experiment, but it seemed to really jump into the second one and kept playing until I terminated the experiment.
If I were going to do it a third time, I'd probably create objects and give a modern agent fetch quests and other goals, and see how well it independently can handle that.
I've also done a very truncated run of a visual novel before, and it was fascinating how "emotional" was. They did a very good job of portraying a human reacting to the story.
Conversely, they absolutely hated hidden rules in Mao.
Wordle would probably be a fun one. Definitely open to suggestions - I just got the harness in place and have been thinking about what to do next.
https://m.youtube.com/watch?v=11sR4va6CXs
Side note: I think we will see an explosion of this type of games. I am naming this genre tamagochi-girlfriend, remember where you heard it first :)
It is entertaining, just in a different way.
https://sullla.com/civ4survivorindex.html
Could be fun - will the AI model get stuck on the same things I did? How does it overcome obstacles? Will it try to break the game to power through?
I see this trope fairly often, i.e. the assumption that an LLM would need to have been trained on <exact thing it is being asked to solve>. Now, while I do have a moderate amount of background in AI, I am definitely not an expert on LLMs as such. I would be interested to hear someone's take, who does work actively in LLM research. Can they generalise "well enough"? They certainly seem to be able to do so, from my anecdata, and I don't believe "training explicitly for every possible scenario" would have scaled even to today's state.
I’m no more surprised that an LLM can solve a Rubik’s cube than it can send an HTTP request.
What changed between Opus 4.6 and Fable and the GPT 5.* models released since?
The LLM models can not reason about a red or white piece on the opposite side and how to move it into place.
Here is just a small list of prompts I tried with Opus 4.6. [0]
[0] https://github.com/adam-s/rubiks-cube/tree/main/prompts/vari...
At the top, it shows the thinking tokens output sliding across the rendered cube solving for 1, 2, and 3 shuffle turns. If you scroll all the way to the bottom it shows my best effort solving for n shuffles on a random cube.
Opus 4.6 HAS BEEN trained on all the known algorithms, but that is worthless, because it is not capable of reasoning about spacial relationships. In order for it to work, it needs to specifically be trained to solve a Rubik's Cube.
Maybe having been trained to solve it, it will be able to apply it other spacial problems in math which are extremely analogous. Nonetheless, that doesn't change the fact that an LLM model can't reason about space, time, or the consequences of its actions.
Sometimes I think that reasoning is only imagination, like Mister Rogers. That reasoning is just playing out the consequences of our actions in imagination. When looking at the reasoning tokens, it seems the LLM models are beginning to imagine also.
[0] https://github.com/adam-s/rubiks-cube/tree/main/prompts/vari...
[1] https://adamsohn.com/reliably-incorrect/
If you don't have an MCP server the AI agent might try to figure out how to talk to the game using the above ideas. But at this point you might as well ask it to help you write one.
> I know someone who tried the "aibot plays pokemon" thing... From what I saw, even if you frame advance every single frame, they still don't seem to grasp the concept of "I need to hold down this button for a few frames until x happens"...
> There's no concept of time, just a never ending state machine thats constantly changing state.
The LLM's were terrible at poker.
Like the World Cup.
The LLM does not have fun, because the LLM is not alive.
https://wordit.org/
It made forward progress in the Figure 8 circuit after I helped it through a menu but kept slamming into a wall so it wasn't on track to win in less than an hour.
Also got it to play Age of Empires: Age of Kings using the same technique but it failed to click on anything.
DS specifically is very fun because it's touch based but the UI components aren't accessible. So it is extremely challenging for LLM's spatial reasoning skills.
I want to improve the harness more and have the LLM dynamically create its own tools based on drawing grid box overlays on a screen in a feedback loop, so it can say "click on the 'end turn'" button instead of "click 240,320" and it would 'just work' in any game.
Unfortunately haven't had the time due to work at my day job and needing to clean out my apartment.
I also am personally curious how the GPT models (which advertise better computer use, etc.) would do as compared to Claude.
Building your own models for it would be an eye-opener though. Learn a lot.