Grandmaster-Level Chess Without Search

1. searchless_chess

   1 3 580 5.0 Python

   Grandmaster-Level Chess Without Search

   

   This repository provides an implementation of our paper Grandmaster-Level Chess Without Search. https://arxiv.org/abs/2402.04494

   The recent breakthrough successes in machine learning are mainly attributed to scale: namely large-scale attention-based architectures and datasets of unprecedented scale. This paper investigates the impact of training at scale for chess. Unlike traditional chess engines that rely on complex heuristics, explicit search, or a combination of both, we train a 270M parameter transformer model with supervised learning on a dataset of 10 million chess games. We annotate each board in the dataset with action-values provided by the powerful Stockfish 16 engine, leading to roughly 15 billion data points. Our largest model reaches a Lichess blitz Elo of 2895 against humans, and successfully solves a series of challenging chess puzzles, without any domain-specific tweaks or explicit search algorithms. We also show that our model outperforms AlphaZero's policy and value networks (without MCTS) and GPT-3.5-turbo-instruct. A systematic investigation of model and dataset size shows that strong chess performance only arises at sufficient scale. To validate our results, we perform an extensive series of ablations of design choices and hyperparameters.

2. InfluxDB

   www.influxdata.com featured

   InfluxDB – Built for High-Performance Time Series Workloads. InfluxDB 3 OSS is now GA. Transform, enrich, and act on time series data directly in the database. Automate critical tasks and eliminate the need to move data externally. Download now.

   

3. lila

   2 825 16,756 10.0 Scala

   ♞ lichess.org: the forever free, adless and open source chess server ♞

   

   > I think lichess is typically ~300 points above chess.com.

   Yeah, no. They are two different rating systems with different curves, there isn't a fixed difference you can apply. At the high end of the scale lichess ratings are below, not above, chess.com ratings. E.g. magnus carlsen 3131 blitz on lichess [0], 3294 blitz on chess.com [1].

   This website [2] tries to translate between the sites, and figures that a 2925 lichess blitz rating (the closet to the one reported in the paper of 2895) translates to 3000 chess.com.

   [0] Multiple accounts but this is the one I found with the most blitz games: https://lichess.org/@/DrNykterstein/perf/blitz

   [1] https://www.chess.com/member/magnuscarlsen

   [2] https://chessgoals.com/rating-comparison/#lichesschesscom

4. chessmate

   3 3 63 0.0 Java

   Chess AI in Java - 2005 High School Project

   

5. Stockfish

   4 154 13,203 9.7 C++

   A free and strong UCI chess engine

   

   My point is that if the computer never flags it will have an inherent advantage in low time controls. If not, why not just test it in hyperbullet games? Games where humans flag in a drawn or winning position need to be excluded, otherwise it’s unclear what this is even measuring.

   And limited depth games would not have been difficult to run. You can run a limited search Stockfish on a laptop using the UCI protocol: https://github.com/official-stockfish/Stockfish/wiki/UCI-%26...

6. chess-transformers

   5 4 126 5.5 Python

   Teaching transformers to play chess

   

   If anyone is looking to get into chess neural nets, I highly recommend this repo - https://github.com/sgrvinod/chess-transformers

   It uses paradigmatic PyTorch with easy to read code, and the architecture is similar to the current best performing chess neural nets.

7. KataGo

   6 51 4,024 9.1 C++

   GTP engine and self-play learning in Go

   

   https://github.com/lightvector/KataGo/blob/master/docs/Analy...

   You can see in the release notes a few screenshot examples where a particular move changes likelihood as you get to higher-level play: https://github.com/lightvector/KataGo/releases/tag/v1.15.0

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