A framework for writing chess engines in Rust.
Simple! Chess is the greatest thing humans have invented. Computers follow closely ;)
There is lots of knowledge out there about how to write a chess engine, and there is a lot of room for innovation also. Writing a chess engine is fun, but even for the simplest engine there is a lot of complex (and boring) things that have to be implemented first: the UCI protocol communication, the rules, the static exchange evaluator, and many more. Thousands of programmers have been re-implementing those things over and over again.
So, if you want to write your own chess engine, you face an unpleasant choice: You either roll up your sleeves and implement all the hard stuff from scratch, or you take someone else's chess engine and struggle to understand its cryptic, undocumented source code, hoping that it will be general enough to allow modification. This unfortunate situation stifles innovation.
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Modular design. Users can write their own implementations for every part of the chess engine.
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Very good default implementations -- move generation, quiescence search, static exchange evaluation, time management, iterative deepening, multi-PV, aspiration windows, generic transposition table.
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Very complete UCI support (including "searchmoves").
Here is how simple it is to create a chess engine using the framework:
extern crate alcibiades;
use alcibiades::stock::*;
use alcibiades::engine::run_uci;
fn main() {
type Ttable = StdTtable<StdTtableEntry>;
type SearchNode = StdSearchNode<StdQsearch<StdMoveGenerator<SimpleEvaluator>>>;
type SearchExecutor = Deepening<SimpleSearch<Ttable, SearchNode>>;
run_uci::<SearchExecutor, StdTimeManager>("My engine", "John Doe", vec![]);
}
This engine is assembled from the "in stock" implementations of the different framework traits.
In reality, you will probably want to write your own implementations
for some of the framework traits. Thanks to Rust's incredible generic
programming capabilities, you are not limited to implementing only the
methods required by the traits. For example you may write your own
static position evaluator which has a consult_endgame_table
method. Then you will be able to write a search algorithm that uses
this method.
Last but not least, the framework has an extensive documentation.