Chess Engine
Advanced chess engine implementing minimax algorithm with alpha-beta pruning. Features move validation, AI opponent, and game state management.
A sophisticated chess engine implementing the minimax algorithm with alpha-beta pruning optimization. This project demonstrates deep understanding of game theory, tree search algorithms, and computational optimization.
The engine features a complete chess rule implementation, intelligent move ordering, and an evaluation function that considers piece values, positional advantages, and king safety. It can analyze positions up to 8 plies deep in reasonable time.
Tech Stack
Key Features
- Complete chess rules including castling, en passant, and promotion
- Minimax search with alpha-beta pruning
- Move ordering heuristics for faster search
- Positional evaluation considering piece-square tables
- Three difficulty levels with adjustable search depth
- Legal move highlighting and validation
- Game state persistence and move history
Technical Highlights
- Alpha-beta pruning reducing node evaluations by 90%+
- Bitboard representation for efficient move generation
- Transposition tables preventing redundant calculations
- Quiescence search for tactical accuracy
- Iterative deepening for time-controlled play
- Principal Variation search optimization
Architecture
Board Representation
- 64-bit bitboards for each piece type
- Magic bitboards for sliding piece moves
- Zobrist hashing for position identification
- Incremental board state updates
Search Algorithm
- Negamax with alpha-beta framework
- Move ordering: captures, killers, history heuristic
- Null move pruning for position refutation
- Late move reduction for non-tactical moves
Challenges & Solutions
Implementing correct castling and en passant edge cases
Tuning evaluation function weights for balanced play
Debugging search algorithms with non-obvious bugs
Optimizing memory usage for deep search trees
Gallery
