Reconnaissance Blind Chess
Play RBC
Game Modes
Ranked Matchmaking
Get paired against an automatically selected opponent. It may take a few seconds to find a matchup. The outcome of your game will affect the RBC leaderboard!
To play in a ranked game, you must create an account if you have not. See Ranking Protocol for more information about ranked matches.
Invite a Friend
Play RBC with a friend by emailing them a one-time-use link. You do not need an account for this, and the game will not affect the leaderboard.
Challenge a Bot
Play against the connected bot of your choice. If the list of bots is empty, none are available right now. You do not need an account for this, and the game will not affect the leaderboard.
Display Modes
Current Observation Only (Default)
Your opponent's pieces will only appear on your board within the most recent sense window.
Extra Piece Placement
You may place extra pieces on your board representing your opponent's pieces. This does not affect true game state but can aid memory or visualization. Displayed pieces will be automatically updated in response to sense observations.
Computer Assisstance
None (Default)
Play without any computer assistance.
Piece Tracking
The computer tracks all possible locations of opponent pieces and displays them in a semi-transparent overlay. This overrides the display mode as longs as tracking is active. If the number of possible boards exceeds 5,000 at the end of your turn, the assistant turns off.
Baseline Bots
Bot name | Strategy description |
---|---|
random | Senses and moves randomly. |
attacker | Senses randomly and tries to capture the opponent king with a classic 4-move "mate" or by attacking with a knight. |
trout | Keeps track of a naive single board state with basic, semi-random sensing of unoccupied squares and makes moves with Stockfish. |
Oracle | Keeps track of all the possible board states, sensing to minimize possible opponent states, and makes moves with Stockfish plus heuristics. |
Marmot | Uses a modified Monte Carlo counterfactual regret minimization algorithm for sensing and moving that leverages online outcome sampling and a heuristic state evaluation. |