I’ve recently hit a milestone on a digital project I’m developing and I am looking for playtesters to help me analyze the core game loop and progression system.
The project is called Crazy Go. My design hypothesis was: Can the deterministic, perfect-information mechanics of the ancient game of Go be used as a compelling combat system for a single-player roguelite?
The Core Concept: Instead of fighting monsters with swords and RNG dice rolls, your “battles” are matches of Go. However, to make it fit the roguelite genre, I had to introduce asymmetry:
The Boards: You don’t play on a standard 19x19 grid. You play on procedurally eroded maps, spirals, islands with choke points, and hexagonal graphs.
The Progression: As you defeat opponents (driven by a custom Neural Network AI), you earn “Komi” (permanent points advantage) and draft Spells (like playing a 2x1 domino piece, or gaining a temporary shield).
A quick note on the AI: While the custom AI currently struggles to fight effectively on the standard and non-standard topologies. I will keep trying different methods to fix the algorithm because the board variations are really fun, but for now, the MVP is fully playable so you can test the concept and see if you enjoy the mechanics!
I am specifically looking for feedback on:
The Roguelite Loop: Do the spell drafts and champion passive abilities feel rewarding?
The Fun Factor: Does playing on a board with choke points and missing corners feel engaging from a puzzle/strategy perspective? Even with the current AI limitations, does the concept hold promise?
The game is fully playable in the browser (no downloads required, no account needed). You can try the MVP here: https://victologo.itch.io/crazy-go
Any feedback on the design theory, the UI, or the mechanics would be incredibly helpful for the next phase of development. Thanks in advance!
Seems like a fun idea. I played some games, too short to really get a feel for it, but I enjoyed the meteor strike raining on the board.
Two things for feedback
UI: clicking away the “game start” overlay already places a stone on the board.
Bot: 9x9 beginner bot doesn’t pass early enough, it plays on for too long until, even after all its stones are gone and the board is almost filled with mine.
Thank you, I’ll bear these improvements in mind for future versions (I think that training the current game algorithm with more 9x9 or 13x13 games on a square board will easily and quickly improve the neural network; I might have it ready in a day, although for non-standard boards the improvements will have to wait a few more weeks).
presumably because he will need his own network anyway,
and he would rather not bother additionally setting up Katago
(Also, using Katago for square boards would result in a large strength difference
between the networks on those boards and the networks on other boards.)
The short answer is: I’ll need my own network anyway for the weird boards, and I wanted to keep the whole thing running locally in the browser rather than relying on a server.
The bigger problem is that I’m developing this as a small indie project on a single home PC, so training a strong AlphaZero-style network for all the different board shapes is way beyond what I can realistically compute right now.
So for the MVP I decided to split the problem:
Standard boards: I’ve switched these to GNU Go 3.8 compiled to WebAssembly (open source). It’s fast, runs entirely in the browser, and gives the normal Go boards a much stronger opponent than my current experimental network.
Crazy boards: These still use my own experimental network, CrazyGoNet V1. It’s definitely not very strong yet, but the important thing is that it can actually play on the irregular boards. Those boards can have holes, missing corners, islands, chokepoints, etc., so a normal Go engine isn’t really an option there.
End-game scoring: I also added automatic Monte Carlo scoring based on Sabaki. It should now detect dead groups and finish the game automatically.
I’ve just uploaded the updated build (v16) to Itch.io.
If you get a chance to try it, I’d be especially interested in whether the standard-board games feel better with the new setup, and whether the difference between the normal and crazy boards feels reasonable.