turbotusmo/src/lib/guesser/reducing.ts

77 lines
2.7 KiB
TypeScript

import { Dict } from "../dict.ts";
import { GuessResult, Info } from "../game/game.ts";
import { Value } from "../utils.ts";
import { Awaitable, enumerate, range, zip } from "../utils.ts";
import { Guessing } from "./guesser.ts";
export class ReducingGuesser implements Guessing {
length;
words;
possibilities;
public constructor(words: Dict) {
this.words = words;
this.length = words.length;
this.possibilities = words.clone();
}
public async guess(try_: (guess: string, known: string) => Awaitable<GuessResult>) {
const guess = this.make_guess();
const result = await try_(guess, "");
if (result.kind === "success") return result;
this.learn(guess, result.informations);
return null;
}
make_guess() {
const letters = [...this.words.letters];
const letters_ranks = [...range(0, this.length)].map(() => new Map(letters.map((l) => [l, { value: 0 }])));
for (const word of this.possibilities.words) {
for (const [index, letter] of enumerate(word)) {
letters_ranks[index].get(letter)!.value += 1;
}
}
const candidates = [...this.words.words];
const scored = candidates.map((word) => [word, score_word_from_ranks(word, letters_ranks)] as const);
const [best] = scored.reduce((a, b) => a[1] > b[1] ? a : b);
return best;
}
learn(word: string, infos: Info[]) {
const to_delete = new Set<string>();
const pos = this.possibilities;
for (const [index, [letter, info]] of enumerate(zip(word, infos))) {
if (info.kind === "there") for (const word of pos.words) if (word[index] !== letter) to_delete.add(word);
if (info.kind === "somewhere") for (const word of pos.words) if (word[index] === letter) to_delete.add(word);
if (info.kind === "abscent") for (const word of pos.words) if (word.includes(letter)) to_delete.add(word);
}
for (const d of to_delete) pos.words.delete(d);
}
}
// note : does not take into account knowledge we already have.
function score_word_from_ranks(word: string, ranks: Map<string, Value<number>>[]) {
let result = 0;
for (const [index, letter] of enumerate(word)) {
// note : bonus for ANY letter.
for (const index_ranks of ranks) {
const letter_rank = index_ranks.get(letter)!.value;
result += letter_rank;
}
// note : bonus for THIS letter.
const index_ranks = ranks[index];
const letter_rank = index_ranks.get(letter)!.value;
result += letter_rank;
}
return result;
}
/*
note : The algorithm must proceed as follow :
1. establish a list of possible words
2. loop :
2.1 for each word, for each letter, estimate by how much this letter cuts possibilities for all three possible outcomes.
(2.1-bis weigts those scores by the frequency of the word ?)
2.2 play the word which individual letters cuts most of the possible space.
*/