SicilianSearch

Inspiration

Just before I began my undergrad, I watched a show called Queens Gambit which changed what went on to do for the next two year. I played so much chess that I made a rating climb all the way to 1800 and even now love playing it. As a computer science engineer, it was always my dream to once make a chess bot stronger than me. Sicilian Search has been a way for me to go after my long lost dream.

What it does

SicilianSearch is a chess engine that uses iterative deepening and a modified alpha-beta pruning algorithm to find optimal moves.

How we built it

We built it by implementing advanced search techniques like transposition tables, quiescence search, and null move pruning, while incorporating an opening book for early game moves.

Challenges we ran into

Our main challenges involved balancing search depth with time constraints and implementing efficient pruning without missing critical moves.

Accomplishments that we're proud of

We're proud of successfully creating a functional chess engine with complex search algorithms and chess-specific optimizations.

What we learned

Through this project, we learned about advanced tree search algorithms, optimization techniques for game trees, and chess-specific heuristics.

What's next for SicilianSearch

Looking ahead, we plan to further optimize our search algorithms, improve the evaluation function, expand the opening book, implement endgame tablebases, and parallelize the search for enhanced performance.

Built With

• c
• movegen