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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import logging
from typing import Optional
from mlagents.envs.communicator_objects.unity_output_pb2 import UnityOutput
from mlagents.envs.communicator_objects.unity_input_pb2 import UnityInput
logger = logging.getLogger("mlagents.envs")
class Communicator(object):
def __init__(self, worker_id=0, base_port=5005):
"""
Python side of the communication. Must be used in pair with the right Unity Communicator equivalent.
:int base_port: Baseline port number to connect to Unity environment over. worker_id increments over this.
:int worker_id: Number to add to communication port (5005) [0]. Used for asynchronous agent scenarios.
"""
def initialize(self, inputs: UnityInput) -> UnityOutput:
"""
Used to exchange initialization parameters between Python and the Environment
:param inputs: The initialization input that will be sent to the environment.
:return: UnityOutput: The initialization output sent by Unity
"""
def exchange(self, inputs: UnityInput) -> Optional[UnityOutput]:
"""
Used to send an input and receive an output from the Environment
:param inputs: The UnityInput that needs to be sent the Environment
:return: The UnityOutputs generated by the Environment
"""
def close(self):
"""
Sends a shutdown signal to the unity environment, and closes the connection.
"""