Features

Key Features & Innovations

ShashChess extends the Stockfish architecture with a suite of unique features designed to enhance strategic understanding, analysis depth, and human-like play. Below are the detailed guides for each core innovation.

🧠 Core Mechanics

• Hybrid MCTS (Monte Carlo Tree Search)

  • An experimental hybrid search algorithm that activates in closed or "Petrosian" positions. It prioritizes probabilistic understanding over brute force to overcome the horizon effect in strategic maneuvering.

• Reinforcement Learning (BrainLearn)

  • A persistent memory system that allows the engine to learn from its own experience. By storing evaluations in a permanent file, ShashChess improves its strength over time, especially in long time controls.

⚙️ Analysis Tools

• Full Depth Threads

  • The ultimate tool for correspondence players. This feature allows specific threads to bypass standard pruning heuristics (LMR, Null Move), forcing a "Brute Force" check to find hidden tactical truths.

• Verbose Trace (Human Analysis)

  • Transforms the engine into a Virtual Coach. Instead of a raw number, this output explains the "Shashin Zone," identifies your "Worst Unit" (Makogonov Principle), and ranks candidate moves by win probability.

🎭 Play Style

• Variety (Human-Like Play)
  • Injects "bounded randomness" into the search to simulate human creativity. From "Standard" mode (diversity without Elo loss) to "Psychological" mode (Tal-like bluffing and aggression).