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...The program works natively with the block state format introduced in 1.13 which enables editing of all world formats. Amulet is built on top of a world converter that converts all world data into a custom superset format. This means that all worlds can be modified in the same way rather than having custom logic for each world format. Amulet comes with a built-in world converter that can be used to convert any world Amulet can open into any other world Amulet can open.

...The system works by building an internal model of the environment and then using that model to simulate possible future outcomes of actions, allowing the agent to learn from imagined experiences rather than only from real interactions. This approach enables the algorithm to efficiently learn policies for decision-making tasks that would otherwise require enormous amounts of data or computational resources. DreamerV3 was designed as a general reinforcement learning framework that can solve diverse tasks using the same configuration of hyperparameters across many environments. In research demonstrations, the algorithm has been shown to perform strongly across more than one hundred control tasks and complex simulated environments.