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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class BrainInfo:
def __init__(self, observation, state, memory=None, reward=None, agents=None, local_done=None,
action=None, max_reached=None):
"""
Describes experience at current step of all agents linked to a brain.
"""
self.observations = observation
self.states = state
self.memories = memory
self.rewards = reward
self.local_done = local_done
self.max_reached = max_reached
self.agents = agents
self.previous_actions = action
class BrainParameters:
def __init__(self, brain_name, brain_param):
"""
Contains all brain-specific parameters.
:param brain_name: Name of brain.
:param brain_param: Dictionary of brain parameters.
"""
self.brain_name = brain_name
self.state_space_size = brain_param["stateSize"]
self.stacked_states = brain_param["stackedStates"]
self.number_observations = len(brain_param["cameraResolutions"])
self.camera_resolutions = brain_param["cameraResolutions"]
self.action_space_size = brain_param["actionSize"]
self.memory_space_size = brain_param["memorySize"]
self.action_descriptions = brain_param["actionDescriptions"]
self.action_space_type = ["discrete", "continuous"][brain_param["actionSpaceType"]]
self.state_space_type = ["discrete", "continuous"][brain_param["stateSpaceType"]]
def __str__(self):
return '''Unity brain name: {0}
Number of observations (per agent): {1}
State space type: {2}
State space size (per agent): {3}
Number of stacked states: {4}
Action space type: {5}
Action space size (per agent): {6}
Memory space size (per agent): {7}
Action descriptions: {8}'''.format(self.brain_name,
str(self.number_observations), self.state_space_type,
str(self.state_space_size), str(self.stacked_states),
self.action_space_type,
str(self.action_space_size),
str(self.memory_space_size),
', '.join(self.action_descriptions))