Partial Information Games

🧠 **Why is this game so much harder for a computer than Chess or Go?**

Chess and Go are games of **perfect information** — both players see the whole board. Hugely complex, but nothing is hidden. The tougher frontier for AI is **imperfect information*, where you can’t* see what your opponent has and must reason under uncertainty — like Poker: you weigh

what they might be holding (and what they think *you* hold), and you bluff.

**That’s Tactico.** Each player commands 40 hidden-rank pieces. You see *where* the enemy is — but not *what*; a piece reveals itself only when it fights. Capture their flag before they capture yours. With every rank hidden, each move is memory, deduction and bluff, and the possible enemy setups are astronomical — which is exactly what makes it so hard.

For this project I trained a neural net to play it: **imitation learning** on tens of thousands of human games, then **self-play reinforcement learning** over millions of games — converging toward a **Nash equilibrium**, a strategy no opponent can exploit. It plays shockingly well.

**So… can you beat it?** Most people can’t. 👀

▶️ **Browser** — free, no signup: https://tactico-4fhpquk6aq-uc.a.run.app/

📱 **Android early beta** — the enhanced, best-supported version (play a friend offline, even in

airplane mode): join https://groups.google.com/g/tactico-testers/about → then become a tester:

https://play.google.com/apps/testing/com.tactico.app

Tell me how many moves you last 😄