Analysis and Comparison of Chess Algorithms
Date Issued
2023-07
Author(s)
Trajkoska, Vesela
Dimeski, Gjorgji
Abstract
In this paper we analyze the results of three different
algorithms programmed for playing chess – genetic algorithm,
Monte Carlo, and Minimax. The algorithms are implemented in
Python through 5 players that play chess against the Stockfish
engine, each for 10 games, after which their Elo rating, game
evaluation, game status, and time per move are compared. The
results show that the algorithms cannot compare to an extensively
trained and optimized chess engine such as Stockfish, and only
2 games of 50 total were won by the Minimax algorithm. There
were no draws. The genetic algorithm is very fast, with less
than a second needed for each move, while the other two are
much slower, with times sometimes reaching over a minute. The
Minimax algorithm’s speed decreases over time, while the Monte
Carlo algorithms’ speeds increase over time.
algorithms programmed for playing chess – genetic algorithm,
Monte Carlo, and Minimax. The algorithms are implemented in
Python through 5 players that play chess against the Stockfish
engine, each for 10 games, after which their Elo rating, game
evaluation, game status, and time per move are compared. The
results show that the algorithms cannot compare to an extensively
trained and optimized chess engine such as Stockfish, and only
2 games of 50 total were won by the Minimax algorithm. There
were no draws. The genetic algorithm is very fast, with less
than a second needed for each move, while the other two are
much slower, with times sometimes reaching over a minute. The
Minimax algorithm’s speed decreases over time, while the Monte
Carlo algorithms’ speeds increase over time.
Subjects
File(s)![Thumbnail Image]()
Loading...
Name
CIIT2023_paper_5.pdf
Size
8.97 MB
Format
Adobe PDF
Checksum
(MD5):871685aa953e3250420763793a89eea1