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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53 行
1.6 KiB

using UnityEngine;
using System.Collections.Generic;
using System;
using Unity.MLAgents.Actuators;
using Unity.MLAgents.Sensors;
namespace Unity.MLAgents.Policies
{
/// <summary>
/// The Remote Policy only works when training.
/// When training your Agents, the RemotePolicy will be controlled by Python.
/// </summary>
internal class RemotePolicy : IPolicy
{
int m_AgentId;
string m_FullyQualifiedBehaviorName;
ActionSpec m_ActionSpec;
ActionBuffers m_LastActionBuffer;
internal ICommunicator m_Communicator;
/// <inheritdoc />
public RemotePolicy(
ActionSpec actionSpec,
string fullyQualifiedBehaviorName)
{
m_FullyQualifiedBehaviorName = fullyQualifiedBehaviorName;
m_Communicator = Academy.Instance.Communicator;
m_Communicator.SubscribeBrain(m_FullyQualifiedBehaviorName, actionSpec);
m_ActionSpec = actionSpec;
}
/// <inheritdoc />
public void RequestDecision(AgentInfo info, List<ISensor> sensors)
{
m_AgentId = info.episodeId;
m_Communicator?.PutObservations(m_FullyQualifiedBehaviorName, info, sensors);
}
/// <inheritdoc />
public ref readonly ActionBuffers DecideAction()
{
m_Communicator?.DecideBatch();
var actions = m_Communicator?.GetActions(m_FullyQualifiedBehaviorName, m_AgentId);
m_LastActionBuffer = actions == null ? ActionBuffers.Empty : (ActionBuffers)actions;
return ref m_LastActionBuffer;
}
public void Dispose()
{
}
}
}