Tactical Complexity • Komodo MC vs Leela Chess Zero • Computer Game (2019) • QCD (D53)

Komodo MC (Monte Carlo) was a groundbreaking variant of the traditional Komodo chess engine developed by Mark Lefler and GM Larry Kaufman. Unlike conventional engines that use alpha-beta search, Komodo MC employed Monte Carlo Tree Search, an innovative approach that competed in top-level computer chess tournaments during 2018-2019.

Lc0 (Leela Chess Zero) is a neural network-based engine inspired by DeepMind’s AlphaZero. The project uses distributed computing for self-learning through reinforcement learning, making it fundamentally different from traditional brute-force engines. During early 2019, Lc0 was rapidly improving and becoming competitive with the world’s strongest engines.

This game took place on February 7, 2019, likely during computer chess competition play (possibly TCEC or CCC events). The matchup represented a fascinating clash between two MCTS-based approaches to chess.

The game opened with a Queen’s Gambit Declined (1.c4 e6 2.d4 Nf6 3.Nc3 d5 4.Bg5 Be7). Black deviated from book on move 8 with 8…h6, and the position evolved into a complex strategic battle.

The early middlegame saw Komodo gain some initiative, but Lc0 demonstrated the positional understanding that neural networks are known for. On move 13, Black played the interesting 13…b5, pushing for queenside counterplay. Komodo’s 14.Qc2 was marked as inaccurate, and Black capitalized with 14…b4.

A critical tactical sequence erupted around moves 19-21. After 19.Ndc3, Lc0 unleashed 19…Rxe3, sacrificing the exchange to destroy White’s pawn structure and create attacking chances. Following 20.Nf4 Rxc3 21.Qh8+ Ke7 22.Re1+ Be6, Komodo’s King hunt petered out, and material remained roughly balanced but with Black holding better piece coordination.

The position transitioned into a complex endgame where Lc0’s positional prowess shone. Black’s connected passed Pawns on the queenside, particularly the advanced b-pawn and c-pawn, became increasingly dangerous. Komodo struggled to coordinate its pieces effectively against these threats.

Around move 38, the game reached a critical juncture with 38…b2, creating an unstoppable Pawn on the second rank. Despite Komodo’s attempts to generate counterplay with 42.Rh2 and later Pawn pushes, Lc0 maintained a precise technique.

The endgame demonstrated Lc0’s calculating strength. Even when Stockfish analysis suggested moves like 50…Kb4 would have been stronger than 50…f6, Lc0 maintained winning chances through patient maneuvering. The final phase saw Lc0 orchestrate a beautiful conversion, advancing its passed Pawns while keeping Komodo’s pieces tied down.

The decisive moment came in the final moves when Black’s Pawns became unstoppable. After 79.Rxg2 b1=Q 80.Bxb1+ Kxb1, the position simplified to a winning King and Pawn endgame for Black. Komodo resigned after 84.Rxa2 Kxa2, recognizing that Black’s Pawns would inevitably promote.

This victory showcased Lc0’s characteristic strengths: deep positional understanding, patient maneuvering, and technical precision in converting advantages—hallmarks of neural network play that made it a formidable competitor against traditional engines.