Spaces:
Sleeping
Sleeping
File size: 2,675 Bytes
ac5cfba |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 |
# Copyright (c) Meta Platforms, Inc. and affiliates.
# All rights reserved.
"""Base class for modular reward components."""
from abc import ABC, abstractmethod
from typing import Any, Dict
class BaseRewardComponent(ABC):
"""
Abstract base class for reward components.
Each reward component calculates a specific aspect of the reward signal
(exploration, badges, levels, etc.) and can be enabled/weighted via config.
Attributes:
name: Unique identifier for this reward component.
weight: Scaling factor applied to calculated reward.
enabled: Whether this component is active.
Example:
>>> class MyReward(BaseRewardComponent):
... def calculate(self, state, prev_state):
... return state["score"] - prev_state.get("score", 0)
>>>
>>> reward = MyReward(weight=2.0)
>>> reward.calculate({"score": 100}, {"score": 50})
100.0 # (100 - 50) * 2.0
"""
def __init__(self, name: str, weight: float = 1.0, enabled: bool = True):
"""
Initialize reward component.
Args:
name: Unique identifier for this component.
weight: Scaling factor for reward (default 1.0).
enabled: Whether component is active (default True).
"""
self.name = name
self.weight = weight
self.enabled = enabled
self._cumulative = 0.0
@abstractmethod
def calculate(
self, state: Dict[str, Any], prev_state: Dict[str, Any]
) -> float:
"""
Calculate reward for this component.
Args:
state: Current game state dictionary.
prev_state: Previous game state dictionary.
Returns:
Unweighted reward value for this component.
"""
pass
def get_reward(
self, state: Dict[str, Any], prev_state: Dict[str, Any]
) -> float:
"""
Get weighted reward if enabled.
Args:
state: Current game state.
prev_state: Previous game state.
Returns:
Weighted reward if enabled, 0.0 otherwise.
"""
if not self.enabled:
return 0.0
reward = self.calculate(state, prev_state) * self.weight
self._cumulative += reward
return reward
def reset(self) -> None:
"""Reset component state for new episode."""
self._cumulative = 0.0
@property
def cumulative_reward(self) -> float:
"""Total reward from this component in current episode."""
return self._cumulative
|