Unity 机器学习代理工具包 (ML-Agents) 是一个开源项目,它使游戏和模拟能够作为训练智能代理的环境。
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105 行
4.3 KiB

import json
import numpy as np
from .exception import UnityEnvironmentException
import logging
logger = logging.getLogger("unityagents")
class Curriculum(object):
def __init__(self, location, default_reset_parameters):
"""
Initializes a Curriculum object.
:param location: Path to JSON defining curriculum.
:param default_reset_parameters: Set of reset parameters for environment.
"""
self.lesson_length = 0
self.max_lesson_number = 0
self.measure_type = None
if location is None:
self.data = None
else:
try:
with open(location) as data_file:
self.data = json.load(data_file)
except IOError:
raise UnityEnvironmentException(
"The file {0} could not be found.".format(location))
except UnicodeDecodeError:
raise UnityEnvironmentException("There was an error decoding {}".format(location))
self.smoothing_value = 0
for key in ['parameters', 'measure', 'thresholds',
'min_lesson_length', 'signal_smoothing']:
if key not in self.data:
raise UnityEnvironmentException("{0} does not contain a "
"{1} field.".format(location, key))
parameters = self.data['parameters']
self.measure_type = self.data['measure']
self.max_lesson_number = len(self.data['thresholds'])
for key in parameters:
if key not in default_reset_parameters:
raise UnityEnvironmentException(
"The parameter {0} in Curriculum {1} is not present in "
"the Environment".format(key, location))
for key in parameters:
if len(parameters[key]) != self.max_lesson_number + 1:
raise UnityEnvironmentException(
"The parameter {0} in Curriculum {1} must have {2} values "
"but {3} were found".format(key, location,
self.max_lesson_number + 1, len(parameters[key])))
self.set_lesson_number(0)
@property
def measure(self):
return self.measure_type
@property
def get_lesson_number(self):
return self.lesson_number
def set_lesson_number(self, value):
self.lesson_length = 0
self.lesson_number = max(0, min(value, self.max_lesson_number))
def increment_lesson(self, progress):
"""
Increments the lesson number depending on the progree given.
:param progress: Measure of progress (either reward or percentage steps completed).
"""
if self.data is None or progress is None:
return
if self.data["signal_smoothing"]:
progress = self.smoothing_value * 0.25 + 0.75 * progress
self.smoothing_value = progress
self.lesson_length += 1
if self.lesson_number < self.max_lesson_number:
if ((progress > self.data['thresholds'][self.lesson_number]) and
(self.lesson_length > self.data['min_lesson_length'])):
self.lesson_length = 0
self.lesson_number += 1
config = {}
parameters = self.data["parameters"]
for key in parameters:
config[key] = parameters[key][self.lesson_number]
logger.info("\nLesson changed. Now in Lesson {0} : \t{1}"
.format(self.lesson_number,
', '.join([str(x) + ' -> ' + str(config[x]) for x in config])))
def get_config(self, lesson = None):
"""
Returns reset parameters which correspond to the lesson.
:param lesson: The lesson you want to get the config of. If None, the current lesson is returned.
:return: The configuration of the reset parameters.
"""
if self.data is None:
return {}
if lesson is None:
lesson = self.lesson_number
lesson = max(0, min(lesson, self.max_lesson_number))
config = {}
parameters = self.data["parameters"]
for key in parameters:
config[key] = parameters[key][lesson]
return config