✨ The Origin Story
On July 4, 2025, ChessBotBuddies began developing a chess engine with a different goal than most traditional engines.
Rather than relying exclusively on brute-force calculation or purely neural evaluation, Buddy was built as a hybrid system — combining classical chess algorithms with machine-learning techniques to support learning and adaptability.
Buddy started with only the rules of chess and improved through self-play, competing against itself across thousands of games. This process helped it learn tactical motifs, positional ideas, and common structures.
To further refine its play, Buddy was trained using a large collection of historical human chess games. The result is an engine that balances calculation accuracy with pattern recognition — making it a strong but educational opponent.
🧠 How Buddy Thinks
Classical Search
Buddy uses traditional alpha-beta pruning for precise calculation, allowing him to spot tactics like a machine and never miss a beat.
- ✔ Deep calculation depth
- ✔ Efficient pruning of weak lines
- ✔ Tactical precision
Neural Network Evaluation
A custom neural network evaluates positions based on patterns, allowing Buddy to understand strategy like a master and play with human-like intuition.
- ✔ Pattern-based position evaluation
- ✔ Positional understanding
- ✔ Long-term strategic planning
Self-Play Training
Buddy improves over time by playing games against itself to refine its evaluations.
Human Game Analysis
Trained using a large dataset of historical chess games played by strong human players.
📊 At a Glance
👥 Our Mission
Buddy isn’t just an engine — it’s a learning companion. We believe chess is best learned in an environment where mistakes are expected and learning is continuous.
"In chess, every move opens new possibilities. Learning why some paths work better than others is what makes the game rewarding."
Buddy is designed as an educational practice opponent. Playing strength and behavior may vary depending on settings, time control, and game conditions.