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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60 行
1.5 KiB

using System;
using UnityEngine;
using UnityEngine.UI;
using MLAgents;
using MLAgents.SideChannels;
public class FoodCollectorSettings : MonoBehaviour
{
[HideInInspector]
public GameObject[] agents;
[HideInInspector]
public FoodCollectorArea[] listArea;
public int totalScore;
public Text scoreText;
StatsSideChannel m_statsSideChannel;
public void Awake()
{
Academy.Instance.OnEnvironmentReset += EnvironmentReset;
m_statsSideChannel = SideChannelUtils.GetSideChannel<StatsSideChannel>();
}
public void EnvironmentReset()
{
ClearObjects(GameObject.FindGameObjectsWithTag("food"));
ClearObjects(GameObject.FindGameObjectsWithTag("badFood"));
agents = GameObject.FindGameObjectsWithTag("agent");
listArea = FindObjectsOfType<FoodCollectorArea>();
foreach (var fa in listArea)
{
fa.ResetFoodArea(agents);
}
totalScore = 0;
}
void ClearObjects(GameObject[] objects)
{
foreach (var food in objects)
{
Destroy(food);
}
}
public void Update()
{
scoreText.text = $"Score: {totalScore}";
// Send stats via SideChannel so that they'll appear in TensorBoard.
// These values get averaged every summary_frequency steps, so we don't
// need to send every Update() call.
if ((Time.frameCount % 100)== 0)
{
m_statsSideChannel?.AddStat("TotalScore", totalScore);
}
}
}