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182 行
4.8 KiB
182 行
4.8 KiB
using System;
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using UnityEngine;
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using System.Linq;
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using MLAgents;
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using UnityEngine.Serialization;
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public class GridAgent : Agent
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{
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Academy m_Academy;
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[FormerlySerializedAs("m_Area")]
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[Header("Specific to GridWorld")]
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public GridArea area;
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public float timeBetweenDecisionsAtInference;
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float m_TimeSinceDecision;
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[Tooltip("Because we want an observation right before making a decision, we can force " +
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"a camera to render before making a decision. Place the agentCam here if using " +
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"RenderTexture as observations.")]
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public Camera renderCamera;
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[Tooltip("Selecting will turn on action masking. Note that a model trained with action " +
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"masking turned on may not behave optimally when action masking is turned off.")]
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public bool maskActions = true;
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const int k_NoAction = 0; // do nothing!
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const int k_Up = 1;
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const int k_Down = 2;
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const int k_Left = 3;
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const int k_Right = 4;
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public override void InitializeAgent()
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{
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m_Academy = FindObjectOfType<Academy>();
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}
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public override void CollectObservations()
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{
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// There are no numeric observations to collect as this environment uses visual
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// observations.
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// Mask the necessary actions if selected by the user.
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if (maskActions)
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{
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SetMask();
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}
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}
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/// <summary>
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/// Applies the mask for the agents action to disallow unnecessary actions.
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/// </summary>
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void SetMask()
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{
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// Prevents the agent from picking an action that would make it collide with a wall
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var positionX = (int)transform.position.x;
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var positionZ = (int)transform.position.z;
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var maxPosition = (int)m_Academy.FloatProperties.GetPropertyWithDefault("gridSize", 5f) - 1;
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if (positionX == 0)
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{
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SetActionMask(k_Left);
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}
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if (positionX == maxPosition)
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{
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SetActionMask(k_Right);
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}
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if (positionZ == 0)
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{
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SetActionMask(k_Down);
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}
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if (positionZ == maxPosition)
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{
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SetActionMask(k_Up);
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}
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}
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// to be implemented by the developer
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public override void AgentAction(float[] vectorAction)
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{
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AddReward(-0.01f);
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var action = Mathf.FloorToInt(vectorAction[0]);
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var targetPos = transform.position;
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switch (action)
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{
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case k_NoAction:
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// do nothing
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break;
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case k_Right:
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targetPos = transform.position + new Vector3(1f, 0, 0f);
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break;
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case k_Left:
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targetPos = transform.position + new Vector3(-1f, 0, 0f);
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break;
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case k_Up:
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targetPos = transform.position + new Vector3(0f, 0, 1f);
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break;
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case k_Down:
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targetPos = transform.position + new Vector3(0f, 0, -1f);
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break;
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default:
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throw new ArgumentException("Invalid action value");
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}
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var hit = Physics.OverlapBox(
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targetPos, new Vector3(0.3f, 0.3f, 0.3f));
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if (hit.Where(col => col.gameObject.CompareTag("wall")).ToArray().Length == 0)
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{
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transform.position = targetPos;
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if (hit.Where(col => col.gameObject.CompareTag("goal")).ToArray().Length == 1)
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{
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Done();
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SetReward(1f);
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}
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if (hit.Where(col => col.gameObject.CompareTag("pit")).ToArray().Length == 1)
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{
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Done();
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SetReward(-1f);
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}
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}
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}
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public override float[] Heuristic()
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{
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if (Input.GetKey(KeyCode.D))
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{
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return new float[] { k_Right };
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}
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if (Input.GetKey(KeyCode.W))
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{
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return new float[] { k_Up };
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}
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if (Input.GetKey(KeyCode.A))
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{
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return new float[] { k_Left };
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}
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if (Input.GetKey(KeyCode.S))
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{
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return new float[] { k_Down };
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}
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return new float[] { k_NoAction };
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}
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// to be implemented by the developer
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public override void AgentReset()
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{
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area.AreaReset();
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}
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public void FixedUpdate()
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{
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WaitTimeInference();
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}
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void WaitTimeInference()
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{
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if (renderCamera != null)
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{
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renderCamera.Render();
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}
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if (m_Academy.IsCommunicatorOn)
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{
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RequestDecision();
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}
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else
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{
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if (m_TimeSinceDecision >= timeBetweenDecisionsAtInference)
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{
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m_TimeSinceDecision = 0f;
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RequestDecision();
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}
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else
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{
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m_TimeSinceDecision += Time.fixedDeltaTime;
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}
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}
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}
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}
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