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This PR introduces an information based approach to multifidelity, using the Multifidelity Maximum Entropy Search method [Takeno 2020, Folch 2023].

This also converts the existing MultiFidelityStrategy to use a separate MultiFidelityAcquisitionFunction. This allows the acquisition function to be explicitly designed by the user. Also, by using BoTorch-style acquisition functions, we are able to generate batches of proposals by conditioning on pending experiments.

Leaving this as a draft because the information-based method doesn't seem to perform very well, which needs some investigation. I'm open to ideas!

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