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 UnityEngine;
using UnityEngine.UI;
using MLAgents;
using MLAgents.Sensors;
using MLAgents.SideChannels;
public class TennisAgent : Agent
{
[Header("Specific to Tennis")]
public GameObject ball;
public bool invertX;
public int score;
public GameObject myArea;
public float angle;
public float scale;
Text m_TextComponent;
Rigidbody m_AgentRb;
Rigidbody m_BallRb;
float m_InvertMult;
FloatPropertiesChannel m_ResetParams;
// Looks for the scoreboard based on the name of the gameObjects.
// Do not modify the names of the Score GameObjects
const string k_CanvasName = "Canvas";
const string k_ScoreBoardAName = "ScoreA";
const string k_ScoreBoardBName = "ScoreB";
public override void Initialize()
{
m_AgentRb = GetComponent<Rigidbody>();
m_BallRb = ball.GetComponent<Rigidbody>();
var canvas = GameObject.Find(k_CanvasName);
GameObject scoreBoard;
m_ResetParams = SideChannelUtils.GetSideChannel<FloatPropertiesChannel>();
if (invertX)
{
scoreBoard = canvas.transform.Find(k_ScoreBoardBName).gameObject;
}
else
{
scoreBoard = canvas.transform.Find(k_ScoreBoardAName).gameObject;
}
m_TextComponent = scoreBoard.GetComponent<Text>();
SetResetParameters();
}
public override void CollectObservations(VectorSensor sensor)
{
sensor.AddObservation(m_InvertMult * (transform.position.x - myArea.transform.position.x));
sensor.AddObservation(transform.position.y - myArea.transform.position.y);
sensor.AddObservation(m_InvertMult * m_AgentRb.velocity.x);
sensor.AddObservation(m_AgentRb.velocity.y);
sensor.AddObservation(m_InvertMult * (ball.transform.position.x - myArea.transform.position.x));
sensor.AddObservation(ball.transform.position.y - myArea.transform.position.y);
sensor.AddObservation(m_InvertMult * m_BallRb.velocity.x);
sensor.AddObservation(m_BallRb.velocity.y);
sensor.AddObservation(m_InvertMult * gameObject.transform.rotation.z);
}
public override void OnActionReceived(float[] vectorAction)
{
var moveX = Mathf.Clamp(vectorAction[0], -1f, 1f) * m_InvertMult;
var moveY = Mathf.Clamp(vectorAction[1], -1f, 1f);
var rotate = Mathf.Clamp(vectorAction[2], -1f, 1f) * m_InvertMult;
if (moveY > 0.5 && transform.position.y - transform.parent.transform.position.y < -1.5f)
{
m_AgentRb.velocity = new Vector3(m_AgentRb.velocity.x, 7f, 0f);
}
m_AgentRb.velocity = new Vector3(moveX * 30f, m_AgentRb.velocity.y, 0f);
m_AgentRb.transform.rotation = Quaternion.Euler(0f, -180f, 55f * rotate + m_InvertMult * 90f);
if (invertX && transform.position.x - transform.parent.transform.position.x < -m_InvertMult ||
!invertX && transform.position.x - transform.parent.transform.position.x > -m_InvertMult)
{
transform.position = new Vector3(-m_InvertMult + transform.parent.transform.position.x,
transform.position.y,
transform.position.z);
}
m_TextComponent.text = score.ToString();
}
public override void Heuristic(float[] actionsOut)
{
actionsOut[0] = Input.GetAxis("Horizontal"); // Racket Movement
actionsOut[1] = Input.GetKey(KeyCode.Space) ? 1f : 0f; // Racket Jumping
actionsOut[2] = Input.GetAxis("Vertical"); // Racket Rotation
}
public override void OnEpisodeBegin()
{
m_InvertMult = invertX ? -1f : 1f;
transform.position = new Vector3(-m_InvertMult * Random.Range(6f, 8f), -1.5f, -1.8f) + transform.parent.transform.position;
m_AgentRb.velocity = new Vector3(0f, 0f, 0f);
SetResetParameters();
}
public void SetRacket()
{
angle = m_ResetParams.GetPropertyWithDefault("angle", 55);
gameObject.transform.eulerAngles = new Vector3(
gameObject.transform.eulerAngles.x,
gameObject.transform.eulerAngles.y,
m_InvertMult * angle
);
}
public void SetBall()
{
scale = m_ResetParams.GetPropertyWithDefault("scale", .5f);
ball.transform.localScale = new Vector3(scale, scale, scale);
}
public void SetResetParameters()
{
SetRacket();
SetBall();
}
}