New AlphaZero Paper Explores Chess Variants

In a new paper from DeepMind, this time co-written by 14th world chess champion Vladimir Kramnik, the self-learning chess engine AlphaZero is used to explore the design of different variants of the game of chess, with different sets of rules. The paper is titled Assessing Game Balance with AlphaZero

Frontiers AlphaZe∗∗: AlphaZero-like baselines for imperfect information games are surprisingly strong

The Artificial Intelligence Gambit - WorldQuant

Computer Chess: Most Up-to-Date Encyclopedia, News & Reviews

Natural sciences and chess: A romantic relationship missing from higher education curricula - ScienceDirect

New AlphaZero Paper Explores Chess Variants

DeepMind's AlphaZero AI Helps Design New Chess Rules

Understanding AlphaZero Neural Network's SuperHuman Chess Ability - MarkTechPost

Frontiers Learning to Play the Chess Variant Crazyhouse Above World Champion Level With Deep Neural Networks and Human Data

Create AI for your Own Board Game From Scratch — AlphaZero-Part 3, by Haryo Akbarianto Wibowo

AI ruined chess. Now it's making the game beautiful again

New AlphaZero Paper Explores Chess Variants

New AlphaZero Paper Explores Chess Variants

AlphaZero/Kramnik: More variants

IJERPH, Free Full-Text

Create AI for your Own Board Game From Scratch — AlphaZero-Part 3, by Haryo Akbarianto Wibowo