scope_rl.policy.head.ContinuousEvalHead#

class scope_rl.policy.head.ContinuousEvalHead(base_policy, name, random_state=None)[source]#

Class to transform the base policy into a deterministic evaluation policy.

Bases: scope_rl.policy.BaseHead

Imported as: scope_rl.policy.ContinuousEvalHead

Note

To ensure API compatibility with d3rlpy, BaseHead inherits d3rlpy.algos.QLearningAlgoBase. This base class also has additional methods including fit, predict, and predict_value. Please also refer to the following documentation for the methods that are not described in this API reference.

See also

(external) d3rlpy’s documentation about QLearningAlgoBase

Parameters:

  • base_policy (QLearningAlgoBase) – Reinforcement learning (RL) policy.

  • name (str) – Name of the policy.

  • random_state (int, default=None (>= 0)) – Random state. (This is for API consistency.)

Attributes:
random_state

Methods

calc_action_choice_probability(x)

Only for API consistency.

calc_pscore_given_action(x, action)

Only for API consistency.

sample_action_and_output_pscore(x)

Only for API consistency.
sample_action_and_output_pscore(x)[source]#

Only for API consistency.

calc_action_choice_probability(x)[source]#

Only for API consistency.

calc_pscore_given_action(x, action)[source]#

Only for API consistency.

Methods,