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"""Reward configuration module.
This module provides the RewardConfig class which contains configuration
parameters for reward computation in reinforcement learning scenarios.
"""
from dataclasses import dataclass
[docs]
@dataclass
class RewardConfig:
"""Configuration for reward computation settings.
This configuration is used for reward modeling and computation in reinforcement
learning scenarios.
Args:
number_of_bins: Number of bins used for reward discretization or binning.
Defaults to 201.
C_neg: Negative constant used in reward computation. Defaults to -1000.0.
reward_normalizer: Normalization factor for rewards. Defaults to 400.
N_steps_look_ahead: Number of steps to look ahead when computing rewards.
Defaults to 50.
"""
number_of_bins: int = 201
C_neg: float = -1000.0
reward_normalizer: int = 400
N_steps_look_ahead: int = 50