Luna Chess-Engine (LCE) 3.1.7 - new version chess engine for Android


Luna Chess Engine
Luna is a high-performance chess engine written in Rust, designed for efficiency and strength. It combines classical bitboard-based move generation with a state-of-the-art NNUE (Efficiently Updatable Neural Network) evaluation, allowing for deep positional understand in.
Author: Spunc595

Luna Chess-Engine (LCE) JA what's new?
Evaluation: akimbo's material scaling factor, now applied
Luna's embedded NNUE network is akimbo's, used as-is under its MIT license.
akimbo scales the network's output at search time by a factor that depends on
the material left on the board. Luna was not applying it.

The factor lowers evaluations, and lowers them most in the endgame, where the
multiplier reaches its minimum. It is not a uniform rescaling: it depends on
material, which changes inside the search tree at every capture, so it directly
affects exchange decisions.

Two things are established:

It reproduces the reference implementation exactly. With the factor
applied, Luna's evaluation matches akimbo's with zero difference across 2000
positions — checked against an akimbo binary built at the commit that
introduced the network, not against a reimplementation.
It wins games. Accepted by SPRT at 10+0.1, bounds [0, 10],
alpha = beta = 0.05, with zero losses on time.
One thing is not. The obvious explanation — that the network was trained with
the factor active, so its raw output expects to be scaled afterwards — does not
hold: akimbo's own data-generation build disables the factor, and the trainer
applies no output scaling. So this is an empirical search-time correction that
matches the reference engine and measurably gains strength, with the mechanism
still open. It is described here as what it is rather than as what it would be
convenient for it to be.

No Elo figure is published for this change. The SPRT estimate comes from a run
that stopped early, which biases it upward, and an unbiased fixed-length
measurement has not been made.


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