The average number of unique states visited by AlphaZero and Go-Exploit
Por um escritor misterioso
Last updated 05 outubro 2024
Student of Games: A unified learning algorithm for both perfect and imperfect information games
Automatic mechanistic inference from large families of Boolean models generated by Monte Carlo Tree Search
Even Superhuman Go AIs Have Surprising Failure Modes — LessWrong
Discovering faster matrix multiplication algorithms with reinforcement learning
The Evolution of AlphaGo to MuZero, by Connor Shorten
When Alpha Zero is making seemingly bizarre moves in chess is it actually predicting what its opponent will do (calculating possibilities), or is it setting up its own attack/defense based on positional
Spatial state-action features for general games - ScienceDirect
Monte Carlo Tree Search: a review of recent modifications and applications
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Value targets in off-policy AlphaZero: a new greedy backup
Frontiers Automatic mechanistic inference from large families of Boolean models generated by Monte Carlo tree search
The Evolution of AlphaGo to MuZero, by Connor Shorten
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