AlphaZero.jl and alphazero-general

AlphaZero.jl
53
Established
alphazero-general
46
Emerging
Maintenance 6/25
Adoption 10/25
Maturity 16/25
Community 21/25
Maintenance 0/25
Adoption 9/25
Maturity 16/25
Community 21/25
Stars: 1,312
Forks: 147
Downloads:
Commits (30d): 0
Language: Julia
License: MIT
Stars: 87
Forks: 34
Downloads:
Commits (30d): 0
Language: Python
License: MIT
No Package No Dependents
Stale 6m No Package No Dependents

About AlphaZero.jl

jonathan-laurent/AlphaZero.jl

A generic, simple and fast implementation of Deepmind's AlphaZero algorithm.

This tool helps researchers, students, and 'hackers' explore and apply advanced AI game-playing techniques. You input a game's rules and structure, and it trains an AI agent through self-play, producing a highly skilled AI for that game, capable of reaching superhuman performance in complex environments like Chess or Go. It's designed for those who want to understand and experiment with AI decision-making.

AI-research game-AI reinforcement-learning combinatorial-optimization computational-game-theory

About alphazero-general

kevaday/alphazero-general

A fast, generalized, and modified implementation of Deepmind's distinguished AlphaZero in PyTorch.

This project offers a fast, adaptable platform for developing AI agents to master complex board games and strategic challenges. It takes game rules and parameters as input, then outputs a highly performant AI agent capable of playing and winning against human or other AI opponents. This is for AI researchers, game developers, or enthusiasts interested in creating advanced game-playing AIs without building an AlphaZero implementation from scratch.

AI-game-training game-AI-development strategic-game-simulation reinforcement-learning-games board-game-AI

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