43 ms·
Playing chess & go is also search in a large tree of moves leading to particular game states
by thisismyswamp 3y ago
Playing chess & go is also search in a large tree of moves leading to particular game states
- pxeger1 3y agoBut AlphaGo etc don’t use any kind of language-based AI, so LLMs (which this thread was about) are no good.
- thisismyswamp 3y agoThe next step seems to be applying past advances in reinforcement learning with modern transformer based models
- mattsan 3y agoWhich multiple teams are working on - OpenAI (Q*), and Meta just released a reinforcement learning framework
- npsomaratna 3y agoCould you point me towards Meta's reinforcement learning framework? I'd like to see how it stacks up against the OpenAI gym.
- mattsan 3y agoSure thing - https://pearlagent.github.io/ https://pearlagent.github.io/ HN post here: https://news.ycombinator.com/item?id=38564526 https://news.ycombinator.com/item?id=38564526
- npsomaratna 3y agoThank you!
- greysphere 3y agoThe final state in chess is a single* state which yes, then branches out to N checkmate configurations and then N*M one-move-from-checkmates, and so on. (*Technically it's won/lost/draw.) The equivalent final state in theorem proving is unique to each theorem so such a system would need to handle an additional layer-of-generalization.
- ChainOfFools 3y agoIs this how some of the more advanced chess engines work, or even the not so advanced ones, where there's a point at which it stops searching the forward move tree in greatest depth, and instead starts searching backwards from a handful of plausible (gross move limit-bound) checkmate states looking for an intersection with a shallow forward search state?
- zone411 3y agoKind of, but it's calculated offline and then just accessed during the game: https://www.chessprogramming.org/Endgame_Tablebases https://www.chessprogramming.org/Endgame_Tablebases