Re:The Limits of Optimization
by dimatura on Tuesday June 29, 2021 @08:02AM
(#27674647)
I think chess would be a more straightforward example to illustrate the article's point. If you look at old games, they used to be a lot more fun, with more variety and risky, moves; see, e.g., Anderssen's "heroic" style. As the game became better understood, these kind of off-the-wall strategies became less common since they rarely paid off against well-prepared adversaries. And of course, the trend came to a logical -- and more poignant -- conclusion than in baseball, with Deep Blue and other chess AI taking over. I believe a similar story could be told for Go.
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Re:The Limits of Optimization
by throw149102 on Wednesday June 30, 2021 @01:18AM
(#27685154)
I would counter that these off-the-wall approaches have become more common with more advanced chess AIs, i.e. AlphaGo Zero and Leela Chess Zero. They frequently play gambits and other aggressive lines that previous chess engines didn't. I think these limits may just be the growing pains of applying rationality to a game, and in the long term statistics and optimization can lead us to better games in general.