Artificially Unintelligent

Most problems in AI come down to optimization. Neural networks train by minimizing a loss. Good Old-Fashioned AI plays games by maximizing a heuristic evaluation. The architectures look nothing alike, but the engine underneath is the same: pick the parameter (or move) that pushes some number in the right direction.

For a chess engine, that number comes from a "fitness function": a heuristic that takes the board state and produces a score for the position. The AI then prioritizes moves that maximize its fitness while trying to minimize the adversary's. This is the famous minimax algorithm, and it goes something like this:

def minimax(board, depth, maximizing):
    if depth == 0 or board.is_terminal():
        return evaluate(board)

    if maximizing:
        value = float('-inf')
        for move in board.legal_moves():
            child = board.apply(move)
            value = max(value, minimax(child, depth - 1, False))
        return value
    else:
        value = float('inf')
        for move in board.legal_moves():
            child = board.apply(move)
            value = min(value, minimax(child, depth - 1, True))
        return value

We can do something interesting here. We win by maximizing our score and minimizing the opponent's. But what happens if we negate the fitness \(f(x)\), say by returning \(-f(x)\)? We start minimizing our own score and maximizing the opponent's. We start, in effect, trying to lose.

def dumb_evaluate(board):
    return -evaluate(board)

One line. That's the whole thing. The algorithm doesn't change; it still faithfully maximizes whatever score it's given. We just give it a worse score, and it faithfully drives the game off a cliff.

With this, we get some pretty entertaining games. I present to you Artificial Unintelligence.

Smart vs Dumb

Eight hand-picked games where Smart starts at a material deficit, often facing a Black army arranged into a deliberate visual pattern, and still wins. The set is ordered from the most ordinary to the most theatrical. Every game ends in checkmate (1-0).

Standard Match

The control. Standard opening, no FEN setup, no visual pattern, just Smart vs Dumb. Smart wins on g6 with a quiet bishop sacrifice and a queen mate. Sets the baseline before things get strange.

Pawn Cross

Black's king sits dead center inside a small + of pawns. Smart has only K + R against this miniature cross and threads the rook around the arms, stripping pawns one at a time before delivering Ra1#.

Zigzag Fence

Black's pawns form a perfect zigzag fence across ranks 4–7. Smart's queen alone walks the fence end to end, picking off pawns on the diagonal and converging on Qe2#.

Bishop Constellation

Black's eight bishops sit on the long diagonals like a star map; Smart's pawn phalanx sits below them. 36 moves of slow promotion warfare yield four white queens and a final Qc1# from the corner of the board.

Four Knights

Smart starts with K + four knights symmetrically posted on a1/c1/f1/h1; Black has the entire opening army. Knights jig their way into a cooperative net and mate before Black can mobilize a single major piece.

Skull Mask

Black's pieces draw a skull: rooks for eye sockets, queens for temples, knight and bishops for jaw and teeth. Smart's king starts in the corner and tip-toes out while a rook and queen deconstruct each feature, ending Qd5#.

Spiral Vault

Black's pieces spiral outward from the king in a vault formation, a chaos of bishops, knights, rooks and queens stacked on every square of the upper half. Smart's R+B+Q carves a path inward through 27 moves of attrition to Qg7#.

Mosaic Blitz

Black's bishops and knights tile the back two ranks in a perfect checkerboard mosaic. Smart's pawn wave cracks open the mosaic, promotes three queens in five moves, and ends in a queen-and-queen double-mate.