Source code for scml.oneshot.rl.reward

from typing import Any, Protocol, runtime_checkable

from negmas import SAOResponse

from scml.oneshot.awi import OneShotAWI

__all__ = ["RewardFunction", "DefaultRewardFunction"]

[docs] class RewardFunction(Protocol): """ Represents a reward function. Remarks: - `before_action` is called before the action is executed for initialization and should return info to be passed to the call - `__call__` is called with the awi (to get the state), action and info and should return the reward """
[docs] def before_action(self, awi: OneShotAWI) -> Any: """ Called before executing the action from the RL agent to save any required information for calculating the reward in its return Remarks: The returned value will be passed as `info` to `__call__()` when it is time to calculate the reward. """ ...
[docs] def __call__( self, awi: OneShotAWI, action: dict[str, SAOResponse], info: Any ) -> float: """ Called to calculate the reward to be given to the agent at the end of a step. Args: awi: `OneShotAWI` to access the agent's state action: The action (decoded) as a mapping from partner ID to responses to their last offer. info: Information generated from `before_action()`. You an use this to store baselines for calculating the reward Returns: The reward (a number) to be given to the agent at the end of the step. """ ...
[docs] class DefaultRewardFunction(RewardFunction): """ The default reward function of SCML Remarks: - The reward is the difference between the balance before the action and after it. """
[docs] def before_action(self, awi: OneShotAWI) -> float: return awi.current_score
[docs] def __call__(self, awi: OneShotAWI, action: dict[str, SAOResponse], info: float): _ = action return awi.current_score - info