Models package

This package provides implementations of common model architectures used in model-based RL, including probabilistic and deterministic ensembles. All models in the library derive from class mbrl.models.Model. We provide a generic ensemble implementation, mbrl.models.BasicEnsemble, that can be used to produce epistemic uncertainty estimates for any subclass of Model. For efficiency considerations, some specific model implementations also provide their own ensemble implementations, without having to rely on BasicEnsemble. One such model is mbrl.models.GaussianMLP, which can be used as a single model or as an ensemble. Additionally, it can be used as a deterministic model trained with MSE loss, or a parameterized Gaussian with mean and log variance outputs, trained with negative log-likelihood.