That's the problem with vibe-coding, no one will waste time understanding all this slop. You should start smaller with simple games and NO AI used, that's how you learn.
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Yeah, I get that - and I knew it was a long shot trying to find help.
And I totally get what you're saying, and I agree, but if I'm being honest with myself I'm not really trying to become a programmer (I've already tried in the past, before AI - and I've realized I don't have the motivation/persistence/attention span to become a good programmer. I actually changed career paths when I was younger because of it)
Not that this helps, but my goal is the board game - I've been working on this board game for over a decade, on and off - and this is my attempt to make it actually accessible and a shot of actually being played by others. My hope is to maybe get a "good enough" version/demo that is playable. If the board game ever gets enough players, then maybe an actual programmer will come along and create a proper application.
I know that's not really a likely scenario, but it's the best bet I have at the moment without actually paying someone to make it. And I don't have the money to pay someone to make something that is literally just a little hobby/passion project I've been working on. I've made the actual board game Creative Commons in the hopes that maybe someone might find the game interesting and be willing to work on it as a hobby as well.
Ehh, sorry - a long tangent without much substance. But regardless, I appreciate your advice - and it's solid advice, but being honest with myself it likely isn't something I will pursue.
Hi. The game doesn't work for me on mobile sadly so I can't offer any specific suggestions but in general I suggest you have two options...
The basic approach is to write some rules/ heuristics for your AI player (e.g. start with move X, if player does X then do Y, if condition X then do Y). You can probably distil some basics from your own strategy.
An advanced approach is to train a model using e.g. reinforcement learning to figure out it's own policy of which actions to take given the game state. You can use a library like stable baselines for this. You may be lucky though to train your agents by pitching them against one another or you might have to teach them e.g. with the rules-based agent or by having them learn from human-vs-human games.
Yeah (it's not extremely optimized for mobile yet, sorry).
As for the suggestions, thanks - I'll definitely look into that library as well :)