MuZero matches or exceeds AlphaZero-level performance in Go, Chess, Shogi and sets a new state of the art on 57 Atari games by learning a model that directly supports planning rather than reconstructing full environment dynamics.
AlphaZero stopped the search at tree nodes representing terminal states and used the ter- minal value provided by the simulator instead of the value produced by the network
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Mastering Atari, Go, Chess and Shogi by Planning with a Learned Model
MuZero matches or exceeds AlphaZero-level performance in Go, Chess, Shogi and sets a new state of the art on 57 Atari games by learning a model that directly supports planning rather than reconstructing full environment dynamics.