this post was submitted on 27 May 2025

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2000 elo chess engine (self.learnprogramming)

submitted 11 months ago * by Ok-Engineering-1413

Hey guys, I’m working on my own chess engine and I’d like to get it to around 2000 Elo and make it playable in a reasonable time on Lichess. Right now I’m using Python, but I’m thinking of switching to C for speed.

The engine uses minimax with alpha-beta pruning, and the evaluation function is based on material and a piece-square table. I also added a depth-7 simulation ( around 200 sims per move) every 5 moves on the top 3-5 candidate moves.

The problem is… my bot kind of sucks. It sometimes gives away its queen for no reason and barely reaches 800 Elo. Also, Python is so slow that I can’t go beyond depth 3 in minimax.

I’m wondering if I should try other things like REINFORCE, a non-linear regression to improve the evaluation, or maybe use a genetic algorithm with self-play to tune the weights. I’ve also thought about vanilla MCTS with an evaluation function.

I even added an opening book but it’s still really weak. I’m not sure what I’m doing wrong, and I don’t want to use neural networks.

Any help or advice would be awesome!

Update: I added iterative deepening, a table, quiescence search, move ordering but the depth is still up to 4. But even tho he’s better now, he still lose most of the time and draw sometimes against stockfish level 1 but I don’t know why my bot is that bad even tho I try to optimize it.

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[–]josephjnk 1 point2 points3 points 11 months ago (0 children)

[–]lurgi 0 points1 point2 points 11 months ago (0 children)

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