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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using System;
using Unity.MLAgents.Sensors;
using UnityEngine;
using UnityEngine.Serialization;
namespace Unity.MLAgents.Integrations.Match3
{
/// <summary>
/// Sensor component for a Match3 game.
/// </summary>
[AddComponentMenu("ML Agents/Match 3 Sensor", (int)MenuGroup.Sensors)]
public class Match3SensorComponent : SensorComponent, IDisposable
{
[HideInInspector, SerializeField, FormerlySerializedAs("SensorName")]
string m_SensorName = "Match3 Sensor";
/// <summary>
/// Name of the generated Match3Sensor object.
/// Note that changing this at runtime does not affect how the Agent sorts the sensors.
/// </summary>
public string SensorName
{
get => m_SensorName;
set => m_SensorName = value;
}
[HideInInspector, SerializeField, FormerlySerializedAs("ObservationType")]
Match3ObservationType m_ObservationType = Match3ObservationType.Vector;
/// <summary>
/// Type of observation to generate.
/// </summary>
public Match3ObservationType ObservationType
{
get => m_ObservationType;
set => m_ObservationType = value;
}
private ISensor[] m_Sensors;
/// <inheritdoc/>
public override ISensor[] CreateSensors()
{
// Clean up any existing sensors
Dispose();
var board = GetComponent<AbstractBoard>();
if (!board)
{
return Array.Empty<ISensor>();
}
var cellSensor = Match3Sensor.CellTypeSensor(board, m_ObservationType, m_SensorName + " (cells)");
// This can be null if numSpecialTypes is 0
var specialSensor = Match3Sensor.SpecialTypeSensor(board, m_ObservationType, m_SensorName + " (special)");
m_Sensors = specialSensor != null
? new ISensor[] { cellSensor, specialSensor }
: new ISensor[] { cellSensor };
return m_Sensors;
}
/// <summary>
/// Clean up the sensors created by CreateSensors().
/// </summary>
public void Dispose()
{
if (m_Sensors != null)
{
for (var i = 0; i < m_Sensors.Length; i++)
{
((Match3Sensor)m_Sensors[i]).Dispose();
}
m_Sensors = null;
}
}
}
}