It is non-trivial to design engaging and balanced sets of game rules. Modern chess has evolved over centuries, but without a similar recourse to history, the consequences of rule changes to game dynamics are difficult to predict. AlphaZero provides an alternative in silico means of game balance assessment. It is a system that can learn near-optimal strategies for any rule set from scratch, without any human supervision, by continually learning from its own experience. In this study we use AlphaZero to creatively explore and design new chess variants.
Last summer, game designer Zach Gage -- best known for mobile titles like Spelltower and Ridiculous FIshing -- went for a walk with a friend, and eventually the discussion turned to chess. His friend had recently taken up the game and become quite proficient, whereas Gage was never able to get into it, despite multiple attempts. This gulf in skill and experience meant that the two couldn't play together in a meaningful way; if they tried, Gage would get crushed, and the match wouldn't be much fun. So he decided to fix the problem. Today sees the launch of Really Bad Chess on iOS.
Russian chess grandmaster Vladimir Kramnik is working with DeepMind's chess program, AlphaZero, to analyze new variants in an attempt to reinvent the popular strategy board game. Vladimir Kramnik, Classical World Chess Champion from 2000 to 2006, has proposed nine new chess variants last Wednesday, September 9. He has worked together with the artificial intelligence (AI) laboratory DeepMind, a subsidiary of Google's parent company Alphabet Inc, to evaluate his proposals with the help of the AlphaZero AI. In a report submitted to Cornell University, Nenad Tomašev, Ulrich Paquet, and Demis Hassabis from DeepMind worked with grandmaster Vladimir Kramnik to assess game balance in the new variations with help from AlphaZero. It defines AlphaZero as "a reinforcement learning system that can learn near-optimal strategies for any rules set from scratch without any human supervision, and provides an in silico alternative for game balance assessment."
In the game between chess and artificial intelligence, Google DeepMind's researchers have made yet another move, this time teaming up with ex-chess world champion Vladimir Kramnik to design and trial new AI-infused variants of the game. With the objective of improving the design of balanced sets of game rules, the research team set out to discover the best tweaks they could possibly give to the centuries-old board game, in an ambitious effort to refresh chess dynamics thanks to AI. The scientists used AlphaZero, an adaptive learning system that can teach itself new rules from scratch and achieve superhuman levels of play, to test the outcomes of nine different chess variants that they pre-defined with Kramnik's help. For each variant, AlphaZero played tens of thousands of games against itself, analyzing every possible move for any given chessboard condition, and generating new strategies and game-play patterns. Kramnik and the researchers then assessed what games between human players might look like if these variants were adopted, to find out whether different sets of rules might improve the game.
TL;DR: Make your game of chess feel a little more luxe with a Crystal Chess Board, on sale for $159.99 -- a 46% savings -- as of March 7. Chess is probably one of the only games that can be just as decorative as it is fun to play. If The Queen's Gambit was your favorite quarantine watch, you can impress all of your friends not only by showing off your skills, but also by displaying this chic chess set. This Crystal Chess Board is made from 100 percent crystal, from the pieces to the board itself. Instead of black and white, the pieces come in both smoke-grey and clear varieties. This game is just as gorgeous to leave out on your end table and use as a decoration as it is to actually play and use for the iconic game itself.