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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163 行
5.2 KiB

using System.Collections;
using UnityEngine;
using MLAgents;
public class HallwayAgent : Agent
{
public GameObject ground;
public GameObject area;
public GameObject symbolOGoal;
public GameObject symbolXGoal;
public GameObject symbolO;
public GameObject symbolX;
public bool useVectorObs;
RayPerception m_RayPer;
Rigidbody m_AgentRb;
Material m_GroundMaterial;
Renderer m_GroundRenderer;
HallwayAcademy m_Academy;
int m_Selection;
public override void InitializeAgent()
{
base.InitializeAgent();
m_Academy = FindObjectOfType<HallwayAcademy>();
m_RayPer = GetComponent<RayPerception>();
m_AgentRb = GetComponent<Rigidbody>();
m_GroundRenderer = ground.GetComponent<Renderer>();
m_GroundMaterial = m_GroundRenderer.material;
}
public override void CollectObservations()
{
if (useVectorObs)
{
var rayDistance = 12f;
float[] rayAngles = { 20f, 60f, 90f, 120f, 160f };
string[] detectableObjects = { "symbol_O_Goal", "symbol_X_Goal", "symbol_O", "symbol_X", "wall" };
AddVectorObs(GetStepCount() / (float)agentParameters.maxStep);
AddVectorObs(m_RayPer.Perceive(rayDistance, rayAngles, detectableObjects));
}
}
IEnumerator GoalScoredSwapGroundMaterial(Material mat, float time)
{
m_GroundRenderer.material = mat;
yield return new WaitForSeconds(time);
m_GroundRenderer.material = m_GroundMaterial;
}
public void MoveAgent(float[] act)
{
var dirToGo = Vector3.zero;
var rotateDir = Vector3.zero;
var action = Mathf.FloorToInt(act[0]);
switch (action)
{
case 1:
dirToGo = transform.forward * 1f;
break;
case 2:
dirToGo = transform.forward * -1f;
break;
case 3:
rotateDir = transform.up * 1f;
break;
case 4:
rotateDir = transform.up * -1f;
break;
}
transform.Rotate(rotateDir, Time.deltaTime * 150f);
m_AgentRb.AddForce(dirToGo * m_Academy.agentRunSpeed, ForceMode.VelocityChange);
}
public override void AgentAction(float[] vectorAction)
{
AddReward(-1f / agentParameters.maxStep);
MoveAgent(vectorAction);
}
void OnCollisionEnter(Collision col)
{
if (col.gameObject.CompareTag("symbol_O_Goal") || col.gameObject.CompareTag("symbol_X_Goal"))
{
if ((m_Selection == 0 && col.gameObject.CompareTag("symbol_O_Goal")) ||
(m_Selection == 1 && col.gameObject.CompareTag("symbol_X_Goal")))
{
SetReward(1f);
StartCoroutine(GoalScoredSwapGroundMaterial(m_Academy.goalScoredMaterial, 0.5f));
}
else
{
SetReward(-0.1f);
StartCoroutine(GoalScoredSwapGroundMaterial(m_Academy.failMaterial, 0.5f));
}
Done();
}
}
public override float[] Heuristic()
{
if (Input.GetKey(KeyCode.D))
{
return new float[] { 3 };
}
if (Input.GetKey(KeyCode.W))
{
return new float[] { 1 };
}
if (Input.GetKey(KeyCode.A))
{
return new float[] { 4 };
}
if (Input.GetKey(KeyCode.S))
{
return new float[] { 2 };
}
return new float[] { 0 };
}
public override void AgentReset()
{
var agentOffset = -15f;
var blockOffset = 0f;
m_Selection = Random.Range(0, 2);
if (m_Selection == 0)
{
symbolO.transform.position =
new Vector3(0f + Random.Range(-3f, 3f), 2f, blockOffset + Random.Range(-5f, 5f))
+ ground.transform.position;
symbolX.transform.position =
new Vector3(0f, -1000f, blockOffset + Random.Range(-5f, 5f))
+ ground.transform.position;
}
else
{
symbolO.transform.position =
new Vector3(0f, -1000f, blockOffset + Random.Range(-5f, 5f))
+ ground.transform.position;
symbolX.transform.position =
new Vector3(0f, 2f, blockOffset + Random.Range(-5f, 5f))
+ ground.transform.position;
}
transform.position = new Vector3(0f + Random.Range(-3f, 3f),
1f, agentOffset + Random.Range(-5f, 5f))
+ ground.transform.position;
transform.rotation = Quaternion.Euler(0f, Random.Range(0f, 360f), 0f);
m_AgentRb.velocity *= 0f;
var goalPos = Random.Range(0, 2);
if (goalPos == 0)
{
symbolOGoal.transform.position = new Vector3(7f, 0.5f, 22.29f) + area.transform.position;
symbolXGoal.transform.position = new Vector3(-7f, 0.5f, 22.29f) + area.transform.position;
}
else
{
symbolXGoal.transform.position = new Vector3(7f, 0.5f, 22.29f) + area.transform.position;
symbolOGoal.transform.position = new Vector3(-7f, 0.5f, 22.29f) + area.transform.position;
}
}
}