What is the estimated skill level of Betafish.js?

Betafish.js is estimated to have an Elo rating between 1800 and 2000. It has successfully defeated Fairy Stockfish Level 6 on Lichess and the 2200 Elo bot on Chess.com.

Does it require any installation?

No, Betafish.js is a web-based tool that runs entirely in your browser using JavaScript, so no download or installation is necessary.

Can I use Betafish.js for position analysis?

Yes, you can input specific board positions using FEN (Forsyth-Edwards Notation) and use the 'AI Move' feature to see how the engine evaluates and plays the position.

Is the source code available?

Yes, the project is open-source and hosted on GitHub by developer Gavin Ong (Strryke), allowing anyone to review the Negamax implementation.

What search techniques does the AI use?

The engine utilizes several advanced techniques including Principal Variation Search (PVS), Quiescence Search to avoid the horizon effect, and Iterative Deepening.

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Games

Free

Betafish.js | Chess AI

A powerful JavaScript-based chess engine using Negamax and Alpha-Beta pruning. Play against an AI with an estimated 2000 Elo rating directly in your browser.

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Rating

Reviews

Upvotes

3 months ago

Listed

Chess

Open Source

JavaScript

Game AI

Chess Engine

Strategy

Browser Game

Chess Analysis

Tool information

Provider

Gavin Ong

Platforms

Web

GitHub

Languages

English

Added to directory

3 months ago

Last updated

about 1 month ago

Rating

Not available

Pricing

Free

About Betafish.js | Chess AI

What the tool does and who it's for

Betafish.js is an open-source chess engine and AI move finder built entirely in JavaScript. Described as an amalgamation of Stockfish and AlphaZero principles, it utilizes the Negamax algorithm with alpha-beta pruning to achieve a competitive Elo rating estimated between 1800 and 2000. Designed for web deployment, it allows users to play against the AI directly in their browser, toggle between different thinking times, and analyze board positions using FEN strings. The engine features advanced search techniques such as Principal Variation Search, Quiescence Search, and Iterative Deepening to calculate optimal moves effectively despite the limitations of the JavaScript environment.

Key capabilities

Negamax Algorithm: Employs a robust searching algorithm with alpha-beta pruning for efficient move calculation.

Variable Thinking Time: Allows users to adjust the AI's calculation duration for different difficulty levels.

FEN Integration: Supports Forsyth-Edwards Notation for importing or exporting specific board positions.

Move History: Includes 'Take Back' functionality to revert moves and explore alternative strategies.

Board Customization: Features the ability to flip the board perspective and reset the game instantly.

AI Move Assistance: Offers an 'AI Move' button that calculates the best next step for the player's current position.

Tapered Evaluation: Uses PeSTO's evaluation function for more accurate mid-game and endgame assessment.

Open Source: The entire codebase is available on GitHub for study, modification, and contribution.

Pricing

Free — plans below

Free

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