🚀 Indirect Encodings, EvoState/EvoParams, gymnax backend

[v0.0.9] - 15/06/2022

Added

• Base indirect encoding methods in experimental. Sofar support for:
  • Random projection-based decodings
  • Hypernetworks for MLP architectures
• Example notebook for infirect encodings.
• Example notebook for Brax control tasks and policy visualizations.
• Adds option to restart wrappers to copy_mean and only reset other parts of EvoState.

Changed

• Change problem wrappers to work with {"params": ...} dictionary. No longer need to define ParameterReshaper(net_params["params"]) to work without preselecting "params". Changed tests and notebooks accordingly.
• Restructured all strategies to work with flax structured dataclass and EvoState/EvoParams. Note that this will require different specification of hyperparameter settings e.g. via es_params = es_params.replace(cross_over_rate=0.9).

from flax import struct
@struct.dataclass
class EvoState:
    ...

• The core strategy API now also works without es_params being supplied in call. In this case we simply use the default settings.
• Moved all gym environment to (still private but soon to be released) gymnax.
• Updated all notebooks accordingly.

Fixed

• Makes ParameterReshaper work also with dm-haiku-style parameter dictionaries. Thanks to @vuoristo.