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Very interesting results. From the paper it sounds like the algorithms you used are very similar to Libratus (pre-solved blueprint + subgame solving). What chan
by vagab0nd 7y ago
Very interesting results. From the paper it sounds like the algorithms you used are very similar to Libratus (pre-solved blueprint + subgame solving). What change made it so that the computation requirement is much lower now?
- noambrown 7y agoThere were several improvements but the most important was the depth-limited search. Libratus would always search to the end of the game. But that's not necessarily feasible in a game as complex as six-player poker. With these new algorithms, we don't need to go to the end of the game. Instead, we can stop at some arbitrary depth limit (as is done in chess and Go AI's). That drastically reduces the amount of compute needed.