dreamerv3 and dreamerv2
DreamerV3 is the successor to DreamerV2, extending discrete world models to diverse continuous control domains beyond Atari, making V2 largely superseded for new projects though both remain available implementations of the same algorithmic lineage.
About dreamerv3
danijar/dreamerv3
Mastering Diverse Domains through World Models
Builds a latent world model using categorical representations that predicts future states and rewards, then trains an actor-critic policy through imagined rollouts. Implemented in JAX with support for diverse environments (Atari, robotics, visual control tasks) and scales efficiently—larger models improve both final performance and sample efficiency without hyperparameter tuning across domains.
About dreamerv2
danijar/dreamerv2
Mastering Atari with Discrete World Models
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