ensemble

Different components for different groups

It is possible to use different algorithms and models for different agent groups.

In this folder, we provide examples on how to do this.

Ensemble algorithm

Ensemble algorithms take as input a dictionary mapping group names to algorithm configs:

from benchmarl.algorithms import EnsembleAlgorithmConfig, IsacConfig, MaddpgConfig

algorithm_config = EnsembleAlgorithmConfig(
    {"agent": MaddpgConfig.get_from_yaml(), "adversary": IsacConfig.get_from_yaml()}
)

Important: All algorithms need to be on-policy or off-policy, it is not possible to mix the two paradigms.

Ensemble model

Ensemble models take as input a dictionary mapping group names to model configs:

from benchmarl.models import EnsembleModelConfig, GnnConfig, MlpConfig

model_config = EnsembleModelConfig(
        {"agent": MlpConfig.get_from_yaml(), "adversary": GnnConfig.get_from_yaml()}
)

Important: if you use ensemble models with sequence models, make sure the ensemble is the outer layer (you cannot make a sequence of ensembles, but an ensemble of sequences yes).