duo_ai.algorithms.always

Classes

AlwaysAlgorithmConfig	Configuration for the AlwaysAlgorithm, which always returns the same action.
AlwaysAlgorithm	Algorithm that always returns the same action, regardless of input.

Module Contents

class duo_ai.algorithms.always.AlwaysAlgorithmConfig

Configuration for the AlwaysAlgorithm, which always returns the same action.

Parameters:

name (str, optional) – Name of the algorithm class. Default is “always”.

Examples

>>> config = AlwaysAlgorithmConfig()

name: str = 'always'

class duo_ai.algorithms.always.AlwaysAlgorithm(config: AlwaysAlgorithmConfig)

Bases: duo_ai.core.algorithm.Algorithm

Algorithm that always returns the same action, regardless of input.

Examples

>>> algo = AlwaysAlgorithm(AlwaysAlgorithmConfig())

config_cls

train(policy: duo.core.Policy, env: gym.Env, validators: Dict[str, duo.core.Evaluator]) → None

Run the AlwaysAlgorithm training procedure.

This method evaluates the provided policy in the given environment using the specified evaluators. The AlwaysAlgorithm always returns the same action, regardless of the input observation.

Parameters:

• policy (duo.core.Policy) – The policy instance to use for generating actions.

• env (gym.Env) – The environment in which the policy is evaluated.

• validators (dict of str to duo.core.Evaluator) – Dictionary mapping split names to evaluator instances for evaluation.

Return type:

None

Examples

>>> algorithm = AlwaysAlgorithm(AlwaysAlgorithmConfig())
>>> algorithm.train(policy, env, validators)